cancer vaccines - worcester polytechnic institute
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CANCER VACCINES
An Interactive Qualifying Project Report
Submitted to the Faculty of
WORCESTER POLYTECHNIC INSTITUTE
In partial fulfillment of the requirements for the
Degree of Bachelor of Science
By:
____________________ ____________________ ____________________
Leila Camplese Johan Girgenrath Talal Hamza
IQP-43-DSA-5218 IQP-43-DSA-7424 IQP-43-DSA-5103
____________________ ____________________
Michaela Hunter Cole Royer
IQP-43-DSA-7267 IQP-43-DSA-3408
August 13, 2018
APPROVED:
_________________________
Prof. David S. Adams, PhD
WPI Project Advisor
This report represents the work of WPI undergraduate students submitted to the faculty as evidence of
completion of a degree requirement. WPI routinely publishes these reports on its website without
editorial or peer review. For more information about the projects program at WPI, please see
http://www.wpi.edu/academics/ugradstudies/project-learning.html
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ABSTRACT
Cancer vaccines are a type of therapy that uses a patient’s immune system (or components
thereof) to fight the patient’s tumor. Several types of cancer vaccines have been developed, including the
use of therapeutic antibody vaccines, dendritic cell vaccines, tumor-infiltrating lymphocyte vaccines,
chimeric antigen receptor vaccines, and immune checkpoint vaccines. While early vaccine experiments
often failed, recent studies have shown some spectacular successes. The goal of this IQP was to
investigate the field of cancer vaccines, assessing its problems, identifying future trends, and making
recommendations for moving the field forward. Our team performed a review of the current research
literature, and conducted interviews with scientists and physicians who design or use these vaccines. We
found the cancer vaccine field to be complex, but it provides a variety of approaches for potentially
treating a patient’s tumor. In some cases these approaches have already provided complete remissions for
relapsing cancers that would be impossible to treat using any other approach. While each type of therapy
can induce side-effects in a portion of the patients, we agree with our interviewees that the side-effects are
usually minor, transient, and treatable, and are far less severe than attempting to save the patient’s life
from a relapsing fatal cancer.
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TABLE OF CONTENTS
Title Page ……………………………….……………………………………..……. 01
Abstract …………………………………………………………………..…………. 02
Table of Contents ………………………………………………………………..… 03
Acknowledgements …………………………………………………………..…….. 04
Authorship ………………………………………………………….………….…… 06
Project Goals ………………………………………………………………………. 07
Background …………….……………………………………...….………….……. 09
Section-1: Introduction to Cancer ……………………...………………….. 09
Section-2: Introduction to Immunology …………………………………… 12
Section-3: Introduction to Cancer Vaccines ………………………………. 16
Literature Review …………………………………………………………………. 19
Section-1: Therapeutic Antibody Vaccines ……………………………….. 19
Section-2: Dendritic Cell (DC) Vaccines …………….……….………….. 48
Section-3: Tumor-Infiltrating Lymphocyte (TIL) Vaccines ……………… 60
Section-4: Chimeric Antigen Receptor (CAR) Vaccines …….……………. 67
Section-5: Immune Checkpoint Vaccines ………………………………… 79
Methods …………………………………………………………………………… 97
Results/Findings ……………………………..…………………………….……… 99
Conclusions and Recommendations ………..…………..…………………….…… 112
Appendix ……………………………………………………………………….…. 116
Sample Questions …………………….….…………………………….…. 116
Interview Preamble …………………………………………………….…. 117
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ACKNOWLEDGEMENTS
This IQP would not have been possible without the support of the individuals listed below. We
thank the following individuals for allowing us to interview them for this IQP project (alphabetical order
by last name):
Dr. Eduard Batlle. Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of
Science and Technology, Baldiri i Reixac 10, 08028 Barcelona, Spain.
Dr. Emily E. Bosco, PhD. Scientist-II, Oncology Research, MedImmune, LLC, Gaithersburg, Maryland
20878, USA.
Dr. Yoon Jin Cha. Department of Surgery, Gangnam Severance Hospital, Yonsei University College of
Medicine, 211 Eonju-ro, Gangnam-gu, Seoul 06273, Republic of Korea.
Dr. Chul Won Choi, MD. Department of Radiation Oncology, Dongnam Institute of Radiological &
Medical Sciences, Jwadong-gil 40, Jangan-eup, Gijang-gun, Busan, 46033, Korea.
Dr. Eleonora DeMartin. Centre Hépatobiliaire, Hôpital Paul Brousse, Groupe Hospitalier Paris Sud,
DHU Hepatinov, RHU Ilite, 12 Avenue Paul Vaillant Couturier, 94800 Villejuif, France.
Dr. Andreas Engert. Professor for Internal Medicine, Hematology & Oncology, Department of Internal
Medicine, University Hospital of Cologne, Kerpener Str 62, 50937 Cologne, Germany. And Chairman of
the German Hodgkin Study Group.
Dr. Vancheswaran Gopalakrishnan. Department of Surgical Oncology, The University of Texas MD
Anderson Cancer Center, Houston, TX 77030, USA.
Dr. Steven C. Katz, MD, FACS. Associate Professor of Surgery, Director, Complex General Surgical
Oncology Fellowship, Director, Office of Therapeutic Development, Roger Williams Medical Center,
825 Chalkstone Avenue, Prior 4 Providence, Rhode Island 02908.
Dr. Linda M. Liau, MD. University of California Los Angeles (UCLA) David Geffen School of
Medicine & Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA.
Dr. Christopher H. Lieu, MD. Director, GI Medical Oncology, and Deputy Associate Director for
Clinical Research, University of Colorado Anschutz Medical Campus, Division of Medical Oncology,
1665 Aurora Ct. Mail Stop F-703 | Aurora, Colorado 80045.
Dr. Michael Lim, MD. Professor of Neurosurgery, Oncology, Radiation Oncology, Otolaryngology, and
Institute of NanoBiotechnology, Director of the Brain Tumor Immunotherapy Program, Director of the
Metastatic Brain Tumor Center, Johns Hopkins University School of Medicine, 600 N. Wolfe Street,
Neurosurgery - Phipps 123, Baltimore, MD 21287.
Dr. Frederick L. Locke, MD. Department of Blood and Marrow Transplantation, Moffitt Cancer
Center, Tampa, FL 33612, USA.
Dr. Andrés Morales La Madrid, MD. Unidad de Neuro Oncología Pediátrica, Servicio de Oncología y
Hematología Pediátrica, Hospital St Joan de Déu, Passeig St Joan de Déu, 2, 08950 Esplugues de
Llobregat, Barcelona, Spain. Also: Laboratory of Developmental Cancer, Institut de Recerca Sant Joan
de Déu, Barcelona, Spain.
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Dr. Michael C. Milone. Center for Cellular Immunotherapies, Perelman School of Medicine at the
University of Pennsylvania, Philadelphia, Pennsylvania.
Dr. Michael A. Postow. Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College,
New York.
Dr. Chunjian Qi, MD, PhD. Professor and Director, Medical Research Center, The Affiliated
Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou, 213003, China; Oncology
Institute, The Affiliated Changzhou No.2 People's Hospital of Nanjing Medical University, Changzhou,
213003, China.
Dr. Sergey E. Sedykh. Laboratory of Repair Enzymes, Siberian Branch of Russian Academy of
Sciences Institute of Chemical Biology and Fundamental Medicine, Novosibirsk State University,
Novosibirsk, Russia.
Dr. Erlin Sun. Department of Urology, Tianjin Institute of Urology, The 2nd Hospital of Tianjin Medical
University, Tianjin 300211, PR China.
Dr. Jakub Svoboda. Lymphoma Program, Abramson Cancer Center, University of Pennsylvania,
Philadelphia, PA.
Dr. John M. Timmerman. Division of Hematology & Oncology, Department of Medicine, Center for
Health Sciences, Room 42-121, University of California at Los Angeles, 10833 LeConte Avenue, Los
Angeles, CA 90095-1678.
Dr. Marek Trněný, MD, CSc. Professor and Chairman, 1st Dept Medicine, 1st Fac Medicine, Charles
University, General Hospital, U nemocnice 2, CZ 128 08 Praha, Czech Republic.
Dr. L.I. Zon. Harvard Department of Stem Cell and Regenerative Biology, Harvard Stem Cell Institute,
Harvard University, 7 Divinity Ave (Fairchild Building, Room G53), Cambridge, MA 02138.
Dr. Emese Zsiros. Department of Gynecologic Oncology, Roswell Park Comprehensive Cancer Center,
Buffalo, NY, USA; and Center for Immunotherapy, Roswell Park Comprehensive Cancer Center,
Buffalo, NY, USA.
Anonymous. Department of Hematology-Oncology, Kaohsiung Chang Gung Memorial Hospital,
No.123, Da-Pei Road, Niaosung Dist, Kaohsiung City, Taiwan, R.O.C.
Anonymous. Departments of Microbiology and Immunology, Norris Cotton Cancer Center, Geisel
School of Medicine at Dartmouth, 621 Rubin Building - HB7936; 1 Medical Center Drive, Lebanon, NH,
03756, USA.
Anonymous. Thyroid Cancer Group, Ingham Institute for Applied Medical Research, Liverpool, NSW,
Australia; School of Medicine, Western Sydney University, Campbelltown, NSW, Australia.
In addition to the interviewees listed above, we would also like to thank Dr. David Adams for
serving as project advisor for this IQP. We found Dr. Adams to be invaluable from the very onset of this
project, through concept initiation and managing the team, to the final conclusions. We thank him for his
enthusiasm, dedication, and continued guidance.
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AUTHORSHIP
Author Topics Covered
Johan Girgenrath Therapeutic Antibody Vaccines
Leila Camplese Dendritic Cell Vaccines
Michaela Hunter Tumor-Infiltrating Lymphocyte Vaccines
Talal Hamza Chimeric Antigen Receptor Vaccines
Cole Royer Checkpoint Inhibitor Vaccines
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PROJECT GOALS
Mission Statement and Objectives
Cancer is a collection of related diseases, all sharing the property of uncontrolled cell division. It
can initiate almost anywhere in the human body, and has over one-hundred different variations. At the
cellular level, cancer is a disease caused by DNA mutations and uncontrolled division of abnormal cells
in the body. As a result of these cellular changes, cancer can be difficult to treat. With our increasing
aging population, the number of people in the U.S. dying of cancer has risen over the years. But with
more accurate and sensitive detection techniques, better drugs for blocking cell growth (using a variety of
mechanisms), and more precise surgical tools for removing tumors, the death rates have actually declined
since 1990. Tumor treatments vary widely, depending on the location and type. Treatment options
include chemotherapy (the use of chemical drugs to block DNA replication or other key cancer processes,
including taxanes, anthracyclines, platins), radiation (to kill rapidly dividing cells), surgery (to remove the
tumor), targeted cancer therapy (drugs that interfere with specific molecules a tumor needs to grow), and
biologic therapy (i.e. cancer vaccines, the subject of this IQP).
But despite the advances mentioned above, and the large amount of money provided by the “War
on Cancer” (initiated by the National Cancer Act of 1971), cancer still remains the second leading cause
of death in the U.S., following cardiovascular disease, so better therapies are needed. The subject of this
IQP is a new form of targeted cancer therapy termed “cancer vaccines”. This type of therapy uses the
patient’s own immune system, or components of the immune system (such as antibodies, T-cells,
dendritic cells, etc.), to fight the patient’s tumor. Several types of cancer vaccines have been developed,
and each will be investigated in this IQP with respect to effectiveness and problems:
1) therapeutic antibodies against proteins present on the surface of tumor cells
(mono- specific antibodies, bi-specific antibodies, and antibody-drug conjugates),
2) dendritic cell vaccines,
3) tumor-infiltrating lymphocyte vaccines
4) chimeric antigen receptor vaccines
5) immune checkpoint vaccines
As is the case for all experimental therapies, cancer vaccines are approved for use in cancer
patients only if their tumors do not respond to traditional therapies such as chemotherapy or radiation
treatment. So, the patients assigned to cancer vaccine clinical trials are those with very poor prognosis.
Under these drastic conditions, any successes are worth pursuing. While the early cancer vaccines did not
work well, the past few years have shown some spectacular successes, including complete cancer
remissions for highly refractive tumors. The topic of cancer vaccines has become one of the hottest topics
in all of cancer research. Currently, researchers are racing to expand the use of immuno-therapies to
benefit different types of cancer patients. Hundreds of clinical trials are now underway to see whether
improved responses can be achieved by using combination therapies, each working with a different
mechanism. Advances in rapid and affordable DNA sequencing technologies have allowed the
identification of a patient’s own tumor neo-antigens as targets, creating a form of personalized medicine.
In addition, scientists have determined that the patient’s gut microbiome (type and number of microbes
present in the patient’s GI tract) helps determine whether the patient will respond to therapy.
But these new vaccines still come with problems. They usually cause deleterious side-effects,
they can be very expensive (especially for the personalized vaccines), and they do not work well in all
patients. The overall goal of this IQP project is to document and evaluate this new technology, to
determine which types of cancer vaccines work best, to document their problems, and help prioritize
future directions.
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The specific objectives are to:
1 Develop a comprehensive assessment of the scientific experiments that led to the development
and use of cancer vaccines.
2 Characterize what key scientific stakeholders believe are the strengths, weaknesses, reliability,
usefulness, and cost of this new technology, and any other concerns.
3 Evaluate all of the obtained evidence and prioritize the remaining problems.
4 Recommend potential solutions for remaining problems, and prioritize future experiments.
Notes on Project Risks
1. Potential Risk to the Human Subjects: The risks to the interviewees, if any, should be very
minor. For this type of project, the information requested and disclosed in the interviews will be
technical, or the interviewees own personal opinions. This type of information should not be
harmful if disclosed. This project has no need to request or disclose proprietary information, such
as technical secrets, as this is not needed to accomplish the goals of the project.
2. Justification of Risk: Interviews with human subjects (biomedical researchers) are required to
obtain information for this project beyond a standard review of the existing literature, although
the risk is minor due to the type of information disclosed.
3. Risk Reduction: For this project, risk to the interviewees will be reduced by informing the
subjects that the interview is voluntary (so they can withdraw their response if they feel it might
be risky to divulge the information asked for), they may end the interview at any time, and they
can ignore any question they wish. If we plan to quote an individual in our report, we will first
obtain the interviewee’s permission. Any request for confidentiality will be honored by making
an anonymous quote, or by not citing the information.
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BACKGROUND
Section-1: Introduction to Cancer
Cancer Description and Causes
Cancer is a collection of related diseases, all sharing the property of uncontrolled cell division. It
can initiate almost anywhere in the human body, and has over one-hundred different variations. The extra
cells form growths called tumors. Some cancers form solid tumors, while others, such as leukemia, form
diffuse tumors. Malignant tumors spread into (invade) nearby tissues, or can break off and travel to
distant places in the body through the blood or the lymph system to form new tumors. Benign tumors do
not invade nearby tissues. From the prostate gland, to the thyroid glands, the lungs, or the kidney, these
malignancies symptomatically grow and strongly affect health.
At the cellular level, cancer is a disease caused by DNA mutations and uncontrolled division of
abnormal cells in the body. It has several hallmarks, including: genomic instability, deregulated cell
signaling causing cell division and growth, sustained cell proliferation, resistance to cell death, and
evasion from the patient’s immune system (Hanahan and Weinberg, 2011). As a result of these cellular
changes, cancer can be difficult to treat.
Cancer Prevalence and Survival Rates
According to the Centers for Disease Control, in 2015 (their most recent data) cancer was the
second leading cause of death in the United States, with 595,930 (22.7%) deaths, compared to 633,842
(24.1%) for the number-1 killer heart disease (CDC, 2018). The number of people in the US dying of
cancer has risen over the years with our increasing aging population, but with improved cancer treatments
the death rates have actually declined since 1990 (CBS, 2018). The gap between the number-1 killer and
number-2 killer is decreasing, likely due to the improving survival rates for heart disease patients (CBS,
2018).
Cancer Survival Rates
Cancer survival rates vary widely, from 8%-18% for difficult to treat cancers, such as pancreatic,
lung, or liver cancers, to greater than 65% for easier to treat cancers, such as cancers of the colon, breast,
kidney, and prostate (that grow slowly and are easier to treat if detected early) (Howlader et al.,
2017). Cancer survival rates have improved significantly in the past several decades due to more accurate
and sensitive detection techniques, better drugs for blocking cell growth (using a variety of mechanisms),
and more precise surgical tools to remove tumors.
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Cancer Treatments
Tumor treatments vary widely, depending on the location and type. Benign tumors in a safe area
of the body that do not cause organ disruption are sometimes left alone and watched carefully. If a tumor
begins uncontrolled growth, treatment options include chemotherapy (the use of chemical drugs to block
DNA replication or other key cancer processes, including taxanes, anthracyclines, platins), radiation (to
kill rapidly dividing cells), surgery (to remove the tumor), targeted cancer therapy (drugs that interfere
with specific molecules a tumor needs to grow), and biologic therapy (i.e. cancer vaccines, the subject of
this IQP).
Strong Need for New Cancer Drugs
Despite the advances mentioned above, and the large amount of money provided by the “War on
Cancer” (initiated by the National Cancer Act of 1971), cancer still remains the second leading cause of
death (following cardiovascular disease), so better therapies are needed.
Cited References on Cancer
American Cancer Society (2018) Cancer A to Z. https://www.cancer.org/cancer.html
American Lung Association (2018) Lung Cancer Fact Sheet. http://www.lung.org/lung-health-and-diseases/lung-disease-lookup/lung-cancer/resource-library/lung-
cancer-fact-sheet.html Bajetta E, Del Vecchio M, Bernard-Marty C, Vitali M, Buzzoni R, Rixe O, Nova P, Aglione S, Taillibert
S, Khayat D (2002) Metastatic melanoma: chemotherapy. Seminars in Oncology, 29 (5): 427–445.
Cancer.org (2018) Prostate Cancer Key Statistics. https://www.cancer.org/cancer/prostate-cancer/about/key-statistics.html
Cancer.org (2018) Breast Cancer. https://www.cancer.org/cancer/breast-cancer.html CBS News (2018) The Top Leading Causes of Death in the US. https://www.cbsnews.com/news/the-
leading-causes-of-death-in-the-us/ CDC.org (2018) Leading Causes of Death. Data are for 2015. https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm
Damber JE, Aus G (2008) Prostate Cancer. Lancet, 2008 May 17; 371(9625): 1710-1721. Dong JT (2006) Prevalent mutations in prostate cancer. Journal of Cellular Biochemistry, 2006 Feb 15;
97(3): 433-447. Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell, 2011 Mar 4; 144(5):
646-674.
Healthline.com (2018) What Are the 12 Leading Causes of Death in the United States?
https://www.healthline.com/health/leading-causes-of-death#1
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Leukemia Research Foundation (2018) Leukemia. http://www.allbloodcancers.org/statistics National Cancer Institute (2018) Leukemia. https://www.cancer.gov/types/leukemia Noone AM, Howlader N, Krapcho M, Miller D, Brest A, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis
DR, Chen HS, Feuer EJ, Cronin KA (editors) (2018) SEER Cancer Statistics Review, 1975-2015,
National Cancer Institute. Bethesda, MD. Updated 4-16-2018. https://seer.cancer.gov/csr/1975_2015/
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Background Section-2:
Introduction to Immunology
This IQP focuses on the immune system, so a brief introduction to this topic will aid our
understanding of how cancer vaccines work. The immune system is composed of a network of cells,
tissues, and organs whose main purpose is to protect the body from disease and infection. Cells in the
immune system recognize problems in the body, communicate with other cells, and react to perform
beneficial functions. The immune system is divided into two major sub-divisions: innate immunity and
adaptive immunity.
Main Divisions of the Immune System
Innate immunity is the portion of the immune system that is ready for immediate response when
an infection is first detected. This system includes physical and chemical surface barriers (such as the
skin, sweat, tears, saliva, respiratory tract mucous, stomach acid, and urine) which serve as an initial
barrier to infection (Science Learning Hub, 2010). This system also includes the use of defensive cells,
defensive proteins, inflammation, and fever. The cells involved in innate immunity include: natural killer
cells (NKs), mast cells, eosinophils, basophils, and phagocytic cells [macrophages, neutrophils, and
dendritic cells (DCs)]. These cells recognize molecular patterns present on the surface of bacteria and
fungi, and act to engulf the pathogens (or aid other cells that engulf and kill them) (Vesely et al., 2011).
DCs are also part of the body’s adaptive immune system (see below). If a pathogen is able to survive the body’s innate defenses, the body will eventually react with a
more advanced response to specifically target the pathogen. This adaptive immune system is also known
as the antigen-specific immune response (Spurrell and Lockley, 2014). Antigens are short domains of
amino acids or sugars that are viewed as foreign by the immune system. The adaptive cells of this system
include antigen-presenting cells (APCs), B-lymphocytes (B-cells), and T-lymphocytes (T-cells). APCs
make contact with a pathogen, internalize it, and process selected antigens for presentation on the cell
surface. These presented antigens bind to immature pre-B-cells and pre-T-cells, which then begin to
differentiate and commit to the antigen. Once these cells have matured, they are specific to the antigen
that induced them: B-cells manufacture and secrete antibodies against the antigen into the blood, and
cytotoxic T-cells identify infected cells and kill them. DCs, B-cells, and T-cells are all part of the cancer
vaccine topic (National Cancer Institute, 2018). Some cancer vaccines use DCs isolated from a patient to
prime them against a tumor-specific antigen, then perfuse the DCs back into the patient to induce B-cells
and T-cells to eliminate the tumor. Other cancer vaccines isolate, prime, and perfuse T-cells back into the
patient.
Antigen Presenting Cells (APCs)
As their name implies, APCs are a specialized type of white blood cell that present foreign
antigens on their surface. These presented antigens are recognized by other components of the immune
system, such as B-cells and T-cells, to help them commit to that specific antigen (Wellness, 2015). In this
process, a foreign invader is detected by an APC and engulfed. Proteases inside the APC degrade foreign
antigens on the invader surface into smaller peptides which are then transported to the APC surface where
they combine with either an MHC type-I molecule (professional presentation) or a type-II molecule
(non-professional presentation). This antigen-MHC complex is then recognized by B-cells and T-cells
to help them commit to that particular antigen (Kimball’s Biology Pages, 2013). Professional APCs
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include dendritic cells, macrophages, or B-cells. These cells present their antigens using MHC-I, and are
the only type to activate helper T-cells. Non-professional APCs include fibroblast cells, thymus epithelial
cells, thyroid epithelial cells, glial cells, pancreatic beta cells, and vascular endothelial cells. These cells
present antigens using MHC-II in a weaker type interaction (Garland Science, 2001).
Antibodies
One type of cancer vaccine involves injecting the patient with antibodies directed against the
patient’s tumor cells. Antibodies are proteins secreted by mature B-cells into the bloodstream that
interact with foreign invaders to bring them to the attention of the immune system for
elimination. Antibodies have a “Y” structure (Figure-1) comprised of two long chains and two short
chains. The antibody constant regions (blue in the diagram) dictate which type of immune cell the
antibody engages, while the variable domains (red in the diagram) interact with the foreign antigen.
Figure-1: Diagram of a Typical Antibody Structure. Antibodies have a
general structure that is similar to a “Y”. It contains variable domains (red)
that specifically bind to the foreign antigen, and constant domains (blue) that
dictate which of the body’s immune cells are engaged by the antibody (Murphy
and Weaver, 2016).
The antibody variable region that binds the antigen is unique to each antibody clone (the group of
antibody molecules secreted from a mature plasma cell and all its derivatives). It has been estimated that
the human immune system can produce over 5 x 1013 different types of antibodies (Murphy and Weaver,
2016). The constant regions of the antibody molecules dictate which class the antibody belongs to. There
are five main classes of antibodies: IgA, IgD, IgE, IgG, and IgM. The constant regions remain fairly
conserved within within each class (Vidarsson et al., 2014). The constant region allows the antibody
molecule to interact with effector molecules and phagocytic cells that internalize the antibody-antigen
complex.
Once an antibody binds its antigen, based on its type of constant region, it signals for a specific
effector function to help destroy the pathogen. There are three main paths for destruction: 1)
neutralization (an antibody blocks a binding site keeping the pathogen from entering a cell, 2)
opsonization (the antibody-antigen complex is taken inside a macrophage cell for destruction), or 3)
complement system activation by the constant region (this system signals plasma proteins to bind to and
puncture the pathogen’s membrane, leading to cell lysis, and coats the pathogen’s membrane to attract
phagocytic cells.
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B-Lymphocytes (B-Cells) B-lymphocytes (B-cells) are produced in the bone marrow, the tissue from which they derive
their name. Pre-B-cells recognize a foreign antigen presented by an antigen-presenting cell
(Immunobiology, 2001). This interaction initiates a maturation process that commits the B-cell to
producing antibodies against the antigen. Cytokine hormones and helper T-cells aid the maturation
process, which results in a plasma cell that secretes antibodies. The committed plasma or B-cells are then
clonally expanded to increase their numbers.
Dendritic Cells (DCs)
Dendritic cells (DCs) derive their name from their branched appearance at specific stages of their
development. They are potent “professional” antigen-presenting cells whose main function is to recognize
foreign antigens (usually small epitope domains of proteins) on the surface of invading pathogens (and
sometimes cancer cells), process the antigen within the cell, and then present it on its surface to other cells
of the immune system, such as T-cells and B-cells, so they can help eliminate the tumor. The B-cells and
T-cells interact with the presented antigen to commit to it. Half of the 2011 Nobel Prize in Physiology or
Medicine went to Ralph M. Steinman for “his discovery of the dendritic cell and its role in adaptive
immunity" (The Nobel Prize, 2011). Because of their ability to present antigens to the immune system,
DCs are used in some types of cancer vaccines to induce a patient’s immune response against an antigen
on the surface of a patient’s tumor cell.
T-Cells
T-lymphocytes (T-cells) are a type of nucleated white blood cell that functions in adaptive
cellular immunity. T-cells are distinguished from other lymphocytes, such as B-cells and natural killer
cells (NK cells), by the presence of a T-cell receptor (TCR) on their cell surface which recognizes a
presented antigen and commits the cell against that antigen (Immunobiology, 2001). They are called T-
cells because they mature in the thymus (although some T-cells also mature in the tonsils). Several types
of T-cells exist, each with a different function: helper (CD4+), cytotoxic (CD8+), memory, suppressor,
mucosal, and gamma delta T-cells.
With respect to the topic of cancer vaccines, tumor infiltrating lymphocytes (TILs) are a type
of T-cell found in tumors that help kill it. High levels of TILs in tumors are often associated with a better
clinical outcome for the patient. TILs isolated from tumors usually include both CD4+ (helper T-cells) and
CD8+ (cytotoxic killer T-cells, CTLs). TILs circulate through the bloodstream, recognize the tumor and
infiltrate it. The CD4+ helper T-cells secrete cytokines to boost the immune system. CTLs directly lyse
the tumor cell.
Cited References on Immunology
Cancer Research UK (2018) The immune system and cancer. http://www.cancerresearchuk.org/about-cancer/what-is-cancer/body-systems-and-cancer/the-immune-
system-and-cancer
Immunobiology (2001) The Immune System in Health and Disease. 5th Edition. Chapter-3: Antigen
Recognition by B-Cell and T-Cell Receptors. National Institutes of Health.
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https://www.ncbi.nlm.nih.gov/books/NBK10770/ Murphy K, Weaver C (2016) Janeway’s Immunobiology. 9th Ed. New York NY.
National Cancer Institute (2018) Immunotherapy: Using the Immune System to Treat Cancer. Site was
updated on 2-14-18. https://www.cancer.gov/research/key-initiatives/immunotherapy. Schultz KT, Grieder F (1987) Structure and function of the immune system. Toxicologic Pathology, 1987;
15(3): 262-264.
Science Learning Hub (2010) The Body’s First Line of Defense. Updated 11-2-2010. https://www.sciencelearn.org.nz/resources/177-the-body-s-first-line-of-defence.
Spurrell EL, Lockley M (2014) Adaptive immunity in cancer immunology and therapeutics. E-Cancer Medical Science, 8: 441. DOI: 10.3332/ecancer.2014.441. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4096025/
The Nobel Prize in Physiology or Medicine (2011) https://www.nobelprize.org/nobel_prizes/medicine/laureates/2011/#
Vesely MD, Kershaw MH, Schreiber RD, Smyth MJ (2011) Natural innate and adaptive immunity to
cancer. Annual Review of Immunology, 2011; 29: 235-271. doi: 10.1146/annurev-immunol-031210-101324.
Vidarsson G, Dekkers G, Rispens T (2014) IgG Subclasses and Allotypes: From Structure to Effector
Functions. Frontiers in Immunology, 2014; 5: 520.
Wellness (2018) Antigen-Presenting Cells. https://www.wellness.com/reference/allergies/antigen-
presenting-cells.
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Background Section-3:
Introduction to Cancer Vaccines
The subject of this IQP is a form of targeted cancer therapy, cancer vaccines. This type of
therapy uses the patient’s own immune system, or components of the immune system (such as antibodies,
T-cells, dendritic cells, etc.), to fight the patient’s tumor. Several types of cancer vaccines have been
developed, and each will be investigated in this IQP: 1) injecting cancer neo-antigens (peptides specific to the cancer cell surface) to help the
immune system make antibodies and T-cells against the tumor, 2) injecting therapeutic antibodies against proteins on the surface of tumor cells (mono-
specific antibodies, bi-specific antibodies, and antibody-drug conjugates), 3) injecting dendritic cell vaccines, 4) injecting T-cell vaccines (TILs and CARs), and 5) injecting immune system modulators (such as immune checkpoint inhibitors).
As is the case for all experimental therapies, cancer vaccines are approved for use in cancer
patients only if their tumors do not respond to traditional therapies such as chemotherapy or radiation
treatment. So, patients assigned to cancer vaccine trials tend to be those with very poor prognosis.
Although the early cancer vaccines did not work well, the past few years have shown some spectacular
successes, including some complete cancer remissions for highly refractive tumors. Thus, the topic of
cancer vaccines has become one of the hottest topics in all of cancer research.
The past few years have seen unprecedented clinical successes, rapid drug developments, and
“first-in-kind” treatment approvals from the FDA. In 2016, the American Society of Clinical Oncology
(ASCO) announced “immunotherapy” as the year's top cancer advance, and in 2017 that society named
immunotherapy as its “advance of the year” (Madden, 2018). The society emphasized the rapid pace of
research in this field, emphasizing that “these agents have extended the lives of many patients with late-
stage cancers for which there have been few treatment options” (Madden, 2018). In 2017, approximately
2,000 immuno-therapeutic agents were under development (Schmidt, 2017).
Researchers are racing to expand the use of immuno-therapies to benefit more types of cancer
patients. Hundreds of clinical trials are now underway to see whether improved responses can be achieved
by using a combination of two immunotherapies, each working with a different mechanism. The
number of clinical trials is increasing at an exponential pace, as evidenced by the number of combination
trials with checkpoint inhibitors and another treatment (Figure-2).
Figure-2: Increase in Cancer
Vaccine Clinical Trials. Shown is an
example of the exponential increase in
clinical trials combining a checkpoint
inhibitor vaccine with another
treatment. Diagram is from Schmidt,
2017.
17
Advances in rapid and affordable DNA sequencing technologies have allowed the identification
of a patient’s own tumor neo-antigens as targets, creating a form of personalized medicine. In addition,
scientists have found that the patient’s gut microbiome (type and number of microbes present in the
patient’s GI tract) helps determine whether the patient will respond to therapy.
The breadth of cancers treatable with cancer vaccine combinations has increased in recent years
(Figure-3). Lung cancer, melanoma, breast cancer, lymphoma, kidney cancer, and head and neck cancers
are among the most researched cancers treated with immuno-vaccines.
Figure-3: Main Types of Cancer Treated with Vaccines. Shown are the most
common cancers treated with cancer vaccine combination trials. Diagram is from
Schmidt, 2017.
Problems with Cancer Vaccines While recent years have shown some spectacular successes with cancer vaccines, much still needs
to be done, as these new cancer vaccines come with problems:
1) It remains unclear why only a subset of patients respond to a particular therapy. Does the tumor stop
making the antigen targeted by the therapy, allowing re-growth? Are components of the patient’s immune
system blocking the success of the therapy?
2) Why are the immuno-therapies so expensive? A recent study indicates that the average checkpoint
vaccine in the US costs $150,000, and the average CAR vaccine about $475,000 (Couzin-Frankel,
2018). Who should pay the price for such expensive medicines? 3) Why do most cancer vaccines induce side-effects? Are the side-effects transient and manageable? The overall goal of this IQP is to document and evaluate the technology of cancer vaccines, to document
technique problems and help prioritize future directions.
Cited References for Introduction to Cancer Vaccines
Couzin-Frankel J (2018) Sticker shock. Science, 2018 Mar 23; 359(6382): 1348-1349. doi: 10.1126/science.359.6382.1348.
18
Madden DL (2018) From a Patient Advocate's Perspective: Does Cancer Immunotherapy Represent a
Paradigm Shift? Current Oncology Reports, 2018 Feb 7; 20(1): 8. doi: 10.1007/s11912-018-0662-5.
Schmidt C (2017) Combinations on Trial: By Giving Immunotherapies in Tandem, Researchers Hope to
Broaden the Benefits. Nature, 552: S67–S69. The data in the article was updated on January 10, 2018
in Nature, 553: 155, to correct the number of immunotherapeutic agents in development from
2,400 down to 2,000. doi: 10.1038/d41586-018-00415-9.
19
LITERATURE REVIEW
Section-1: Therapeutic Antibody Vaccines Johan Girgenrath
Cancer Antigens and Neo-Antigens as Antibody Targets
The success of all cancer vaccines depends on the existence of antigens (proteins or sugars, or
portions thereof) on the surface of the cancer cells that can be specifically targeted by the
vaccine. Tumors are caused by mutations in DNA. Some of these mutations alter the expression levels or
types of antigens on the surface of the tumor (Parmiani et al., 2007). New antigens presented on the
tumor surface that are lacking in normal cells are termed neo-antigens (Schumacher and Schreiber,
2015). Neo-antigens can vary from tumor to tumor, and from patient to patient, so they are the subject of
much research in the personalized medicine field.
Tumor cells in the body are poor antigen-presenting cells. Tumor cells are derived from normal
cells by DNA mutation, so the vast majority of the tumor cell DNA is identical to the patient’s normal
cells. Thus, the tumor surface antigens look mostly like “self” to the immune system, and are ignored,
allowing the tumor to grow. Only a small portion of the cancer DNA mutations create neo-antigens
unique to the patient’s tumor, and these provide excellent candidates for cancer vaccine designs. One of
the goals of cancer vaccine research is to develop rapid affordable methods for determining the exact neo-
antigens present in a specific patient’s tumor, and designing a personal vaccine for that patient.
Much research in the cancer vaccine field has focused on identifying specific antigens for
targeting. These antigens should not be found in large quantities in normal cells, to prevent their damage
by the vaccine. Examples include proteins CD19, CD20, or CD22 on the surface of B-cells, which are
targeted by cancer vaccines against B-cell tumors (such as leukemia), overactive B-cells (autoimmune
disorders, transplant rejection), or for killing dysfunctional B-cells. Another well-known example is the
protein Her-2, which is over-expressed on some types of breast cancer cells, and is targeted by the
monovalent cancer vaccine antibody Herceptin (also known as Trastuzumab or Herclon).
Mono-Specific Antibody Vaccines
One type of cancer vaccine consists of injecting the patient with antibodies against the tumor
cell. As mentioned in the Immunology Introduction section, antibodies are proteins secreted by mature
B-cells (plasma cells) into the bloodstream that interact with foreign invaders to bring them to the
attention of the immune system for elimination. Injecting antibodies into a patient is termed passive
immunity. It does not activate the patient’s own immune system to create the antibodies, but instead the
antibodies are produced by a bio-engineering process. The antibodies bind to antigen to create antigen-
antibody complexes, which are then recognized and cleared from body by other cells of the immune
system, such as macrophages or T-cells. The antibodies used in a cancer vaccine can be mono-specific,
bi-specific, or antibody-drug conjugates.
Mono-specific (or monovalent) antibodies recognize only one type of antigen. Most natural
antibodies produced in the human body against an infection are of this type. The variable domains on
both arms of the “Y” shaped antibody recognize the same antigen. For example, the first antibody
20
approved as a cancer vaccine in the U.S. was Rituximab, an antibody against surface protein CD20. This
protein is found on the surface of B-cells, so the antibody is used to treat patients with high B-cell
numbers (leukemia and lymphoma), patients with overactive B-cells (autoimmune disorders, transplant
rejection), or patients with dysfunctional B-cells. Rituximab was initially approved by the FDA in 1997
to treat non-Hodgkin (Maloney et al., 1997). Several studies have used it in clinical trials with various
success. Another example is Inotuzumab, a mono-specific antibody against CD22, used to treat patients
with refractory acute lymphoblastic leukemia (ALL). Perhaps the best known antibody in this category is
Herceptin (also known as Trastuzumab or Herclon), the second antibody approved by the FDA for cancer
treatment in the U.S. Herceptin binds to the HER2/neu receptor, which is over-expressed on some types
of cancer cells (Bange et al., 2001). Herceptin was approved by the FDA in September 1998 for treating
HER2-positive breast cancers, and is now used to treat colorectal and pancreatic cancers (Perez et al.,
2002).
Example of Mono-Specific Antibody Clinical Trials
With respect to clinical trials using mono-specific antibodies, although the treatments in this
category sometimes prolonged a patient’s life, a review of the literature showed that full cancer
remissions have not been that common. Table-I below shows examples of clinical trials done with
mono-specific antibodies.
Table-I: Example Clinical Trials With Mono-Specific Antibody Vaccines
Target
Antigen Cancer Notes Side-Effects Reference
CD20
Low-grade
non-
Hodgkin’s
lymphoma
Phase-III trial on 116 patients, 48%
achieved a measurable tumor response, 6%
achieved complete tumor responses, 76%
achieved ≥20% reduction in tumor volume.
Berinstein et
al., 1998
Indolent B-
cell
lymphoma
Combination trial of Rituximab with
chemotherapy, 40 patient group, 55%
complete remission and 40% partial
remission.
Czuczman,
1999
Stage II-IV
low-grade
non-
Hodgkin’s
lymphoma
39 patients, 54% of the patients showed
objective responses, at 1 year 77% showed
progression-free survival.
The treatment was
well tolerated. Hainsworth,
2000
Aggressive
non-
Hodgkin’s
lymphoma
(NHL)
Rituxan plus chemotherapy combination, 33
patients, 61% of the patients experienced a
“complete response”. 29 of 31 responding
patients remained in remission during a 26
month follow-up period.
The most frequent
adverse events
attributed to the
Rituxan antibody
were fever and chills.
Vose et al.,
2001
Non-Hodgkin
lymphoma
(NHL)
Rituximab, 50 patients, the response rate
after 50 days was 73%, with 10 patients
(20%) in complete remission, 3 patients in
complete remission/unconfirmed, and 23
patients in partial remission.
Colombat et
al., 2001
21
Indolent non-
Hodgkin’s
lymphoma
62 patients, Following a second Rituximab
treatment, the major response rate increased
from 47% to 65%, and the complete
response rate increased from 7% to 27%.
There was no
observable toxicity
with repeat courses of
rituximab.
Hainsworth,
2002
HER-2
Metastatic
breast cancer 222 women, blinded, independent response
evaluation committee identified 8 complete,
and 26 partial responses, providing an
overall response rate of 15%.
The most common
adverse events were
infusion-associated
fever and/or chills
(40% of the patients).
Cobleigh et
al., 1999
Metastatic
breast cancer 234 patients were randomly assigned to
receive standard chemotherapy, and 234
patients were assigned to receive standard
chemotherapy plus trastuzumab. The results
indicated that the addition of trastuzumab
antibody to the chemotherapy regime
provided a longer time to disease
progression (median 7.4 vs 4.6 months;
p<0.001) and a lower rate of death at 1 year
(22% vs 33%, p=0.008).
The most important
adverse event
observed was cardiac
dysfunction (27% in
chemo group versus
13% in the
combination group).
The symptoms were
manageable.
Slamon et
al., 2001
Advanced
breast cancer An international, multicenter, randomized
trial, 1,694 received trastuzumab and 1,693
were controls. At one year, recurring breast
cancer or death was observed in 127 patients
in the trastuzumab group versus 220 in the
control group.
Severe cardiotoxicity
developed in 0.5% of
the women treated
with trastuzumab.
Piccart-
Gebhart et
al., 2005
Breast cancer
patients
27 breast cancer patients were treated with
trastuzumab and chemotherapy. Anti-HER-
2/neu antibodies were detectable in 29% of
the patients before treatment, and in 56% of
the patients during treatment. Of the
twenty-two individuals treated for metastatic
disease, those showing improved clinical
responses had higher levels of HER-2
antibodies.
Taylor et al.,
2007
CD22
Acute
lymphocytic
leukemia
(ALL)
Phase-II clinical trial. The antibody was
conjugated to the toxin calecheamicin to kill
the CD22+ cells. Of the 49 treated patients:
9 (18%) had a complete response, 19 (39%)
had resistant disease, and only 2 (4%) died.
The most frequent
side effects were
fever (20 patients),
hypotension (12
patients), and liver
toxicity (12 patients).
Kantarjian et
al., 2012
22
Acute
lymphocytic
leukemia
(ALL)
Follow-up study, Inotuzumab (a CD22 mAb
bound to toxin calicheamicin), 90 patients,
49 received a single-dose 3-4 weeks, while
41 patients received inotuzumab weekly
every three to four weeks. The overall
response rate was 58%, 19% achieved a
complete response, 30% had a complete
response with no platelet recover (CRp), and
9% had a bone marrow complete recovery.
The response rates were similar between the
two groups.
Some of the adverse
side effects observed
were reversible
bilibrubin elevation,
fever, and
hypotension.
Kantarjian et
al., 2013
EGFR
Non-small-
cell lung
cancer
(NSCLC)
Phase III clinical trial. Treatment with mAb
Cetuximab (binds EGFR) + chemotherapy
(n = 557) vs treatment with chemotherapy
(n = 568). Patients treated with both
cetuximab and chemotherapy survived
several months longer than patients treated
solely with chemotherapy.
10% of patients that
were administered
cetuximab observed
an acne-like rash.
Pirker et al.,
2009
Problems with Monovalent Vaccines
Because tumor cells are mutated patient cells, there are still many similarities between normal
patient cells and tumor cells. As a result, monovalent antibodies that are designed against antigens present
on a tumor cell may also recognize these same antigens on healthy cells, disrupting normal function and
causing off-target effects. In addition, some tumors downregulate expression of the target antigen, or
don’t express it at all. For example, in B-cell cancers, CD22 is present on about 60-90% of B-cell
malignancies, but not in 10-40% of leukemic patients (Hoelzer, 2013). In spite of this, some success has
been achieved with CD19 antibodies for B-cell tumors and leukemia (Naddafi et al., 2015), likely because
CD19 is restricted to the B-cell lineage, and lost B-cells can be replaced in the patient post-cancer
treatment. To be effective, monovalent antibody vaccines need a healthy patient’s immune system to help
clear the cancer cells tagged by the vaccine; binding of the antibody by itself does not kill the cancer cell.
So, monovalent vaccines might not work well in immuno-compromised patients.
References for Monovalent Vaccines
Arlen PM, Gulley JL, Parker C, Skarupa L, Pazdur M, Panicali D, Beetham P, Tsang KY, Grosenbach
DW, Feldman J, Steinberg SM, Jones E, Chen C, Marte J, Schlom J, Dahut W (2006) A randomized
phase II study of concurrent docetaxel plus vaccine versus vaccine alone in metastatic androgen-
independent prostate cancer. Clinical Cancer Research, 2006 Feb 15; 12(4): 1260-1269. Bange J, Zwick E, Ullrich A (2001) Molecular targets for breast cancer therapy and prevention. Nature
Medicine, 2001 May; 7(5): 548-552. Berinstein NL, Grillo-López AJ, White CA, Bence-Bruckler I, Maloney D, Czuczman M, Green D,
Rosenberg J, McLaughlin P, Shen D (1998) Association of serum Rituximab (IDEC-C2B8) concentration
and anti-tumor response in the treatment of recurrent low-grade or follicular non-Hodgkin's lymphoma.
Annals of Oncology, 1998 Sep; 9(9): 995-1001.
23
Bottaro DP, Rubin JS, Faletto DL, Chan AM, Kmiecik TE, Vande Woude GF, Aaronson SA (1991)
Identification of the hepatocyte growth factor receptor as the c-met proto-oncogene product. Science,
1991 Feb 15; 251(4995): 802-804. Cobleigh MA, Vogel CL, Tripathy D, Robert NJ, Scholl S, Fehrenbacher L, Wolter JM, Paton V, Shak S,
Lieberman G, Slamon DJ (1999) Multinational study of the efficacy and safety of humanized anti-HER2
monoclonal antibody in women who have HER2-overexpressing metastatic breast cancer that has
progressed after chemotherapy for metastatic disease. Journal of Clinical Oncology, 1999 Sep; 17(9):
2639-2648. Colombat P, Salles G, Brousse N, Eftekhari P, Soubeyran P, Delwail V, Deconinck E, Haïoun C,
Foussard C, Sebban C, Stamatoullas A, Milpied N, Boué F, Taillan B, Lederlin P, Najman A, Czuczman MS (1999) CHOP plus rituximab chemo-immunotherapy of indolent B-cell lymphoma.
Seminars in Oncology, 1999 Oct; 26(5 Suppl 14): 88-96.
Colombat P, Salles G, Brousse N, Eftekhari P, Soubeyran P, Delwail V, Deconinck E, Haioun C,
Foussard C, Sebban C, Stamatoullas A, Milpied N, Bouè F, Taillan B, Lederlin P, Najman A,
Thièblemont C, Montestruc F, Mathieu-Boué A, Benzohra A, Solal-Céligny P (2001) Rituximab (anti-
CD20 monoclonal antibody) as single first-line therapy for patients with follicular lymphoma with a low
tumor burden: clinical and molecular evaluation. Blood, 2001 Jan 1; 97(1): 101-106.
Furge KA, Zhang Y, Woude GFV (2000) Met receptor tyrosine kinase: enhanced signaling through
adapter proteins. Oncogene, 2000 Nov; 19: 5582-5589.
Hainsworth JD (2000) Rituximab as first-line systemic therapy for patients with low-grade lymphoma.
Seminars in Oncology, 2000 Dec; 27(6 Suppl 12): 25-29.
Hainsworth JD (2002) Rituximab as first-line and maintenance therapy for patients with indolent non-
Hodgkin's lymphoma: interim follow-up of a multicenter phase II trial. Seminars in Oncology, 2002 Feb;
29(1 Suppl 2): 25-29.
Hoelzer D (2013) CD22 monoclonal antibody therapies in relapsed/refractory acute lymphoblastic
leukemia. Cancer, 2013 Aug 1; 119(15): 2671-2674.
Hudis CA (2007) Trastuzumab--mechanism of action and use in clinical practice. New England Journal
of Medicine, 2007 Jul 5; 357(1): 39-51. Kantarjian H, Thomas D, Jorgensen J, Jabbour E, Kebriaei P, Rytting M, York S, Ravandi F, Kwari M,
Faderl S, Rios MB, Cortes J, Fayad L, Tarnai R, Wang SA, Champlin R, Advani A, O'Brien S (2012)
Inotuzumab ozogamicin, an anti-CD22-calecheamicin conjugate, for refractory and relapsed acute
lymphocytic leukaemia: a phase 2 study. Lancet Oncology, 2012 Apr; 13(4): 403-411. Kantarjian H, Thomas D, Jorgensen J, Kebriaei P, Jabbour E, Rytting M, York S, Ravandi F, Garris R,
Kwari M, Faderl S, Cortes J, Champlin R, O'Brien S (2013) Results of inotuzumab ozogamicin, a CD22
monoclonal antibody, in refractory and relapsed acute lymphocytic leukemia. Cancer, 2013 Aug 1;
119(15): 2728-2736.
Lee S, Yang W, Lan KH, Sellappan S, Klos K, Hortobagyi G, Hung MC, Yu D (2002) Enhanced
sensitization to taxol-induced apoptosis by herceptin pretreatment in ErbB2-overexpressing breast cancer
cells. Cancer Research, 2002 Oct 15; 62(20): 5703-5710.
24
Macauley MS, Crocker PR2, Paulson JC (2014) Siglec-mediated regulation of immune cell function in
disease. Nature Reviews Immunology, 2014 Oct; 14(10): 653-666.
Maloney DG, Grillo-López AJ, White CA, Bodkin D, Schilder RJ, Neidhart JA, Janakiraman N, Foon
KA, Liles TM, Dallaire BK, Wey K, Royston I, Davis T, Levy R (1997) IDEC-C2B8 (Rituximab) anti-
CD20 monoclonal antibody therapy in patients with relapsed low-grade non-Hodgkin's lymphoma. Blood,
1997 Sep 15; 90(6): 2188-2195. Merchant M, Ma X, Maun HR, Zheng Z, Peng J, Romero M, Huang A, Yang NY, Nishimura M, Greve J,
Santell L, Zhang Y, Su Y, Kaufman DW, Billeci KL, Mai E, Moffat B, Lim A, Duenas ET, Phillips HS,
Xiang H, Young JC, Woude GFV, Dennis MS, Reilly DE, Schwall RH, Starovasnik MA, Lazarus RA,
Yansura DG (2013) Monovalent antibody design and mechanism of action of onartuzumab, a MET
antagonist with anti-tumor activity as a therapeutic agent. Proceedings of the National Academy of
Sciences of the United States of America, 2013 Aug; 110 (32): 2987-2996.
Naddafi F, Davami F (2015) Anti-CD19 Monoclonal Antibodies: a New Approach to Lymphoma
Therapy. International Journal of Molecular and Cellular Medicine, 2015 Summer; 4(3): 134-151.
Organ SL, Tsao MS, Bono JS (2011) An overview of of the c-MET signaling pathway. Medical
Oncology, 2011 Nov; 3(1): 7-19. Otipoby KL, Draves KE, Clark EA (2001) CD22 regulates B cell receptor-mediated signals via two
domains that independently recruit Grb2 and SHP-1. Journal of Biological Chemistry, 2001 Nov 23;
276(47): 44315-44322.
Parmiani G, De Filippo A, Novellino L, Castelli C (2007) Unique human tumor antigens: immunobiology
and use in clinical trials. Journal of Immunology, 2007 Feb 15; 178(4): 1975-1979. Perez SA, Sotiropoulou PA, Sotiriadou NN, Mamalaki A, Gritzapis AD, Echner H, Voelter W, Pawelec
G, Papamichail M, Baxevanis CN (2002) HER-2/neu-derived peptide 884-899 is expressed by human
breast, colorectal and pancreatic adenocarcinomas and is recognized by in-vitro-induced specific CD4(+)
T cell clones. Cancer Immunology, Immunotherapy, 2002 Jan; 50(11): 615-624. Piccart-Gebhart MJ1, Procter M, Leyland-Jones B, Goldhirsch A, Untch M, Smith I, Gianni L, Baselga J,
Bell R, Jackisch C, Cameron D, et al. Herceptin Adjuvant (HERA) Trial Study Team (2005) Trastuzumab
after adjuvant chemotherapy in HER2-positive breast cancer. New England Journal of Medicine, 2005
Oct 20; 353(16): 1659-1672.
Pirker R, Pereira JR, Szczesna A, Pawel Jv, Krzakowski M, Ramlau R, Vynnychenko I, Park K, Yu CT,
Ganul V, Roh JK, Bajetta E, O’Byrne K, marinis F, Eberhardt W, Stat TGD, Emig M, Gatemeier U
(2009) Cetuximab plus chemotherapy in patients with advanced non-small-cell lung cancer (FLEX): an
open-label randomised phase III trial. The Lancet, 2009 May; 373(9674): 1497-1498. Schumacher TN, Schreiber RD (2015) Neoantigens in cancer immunotherapy. Science, 2015 Apr 3;
348(6230): 69-74. Slamon DJ, Leyland-Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, Fleming T, Eiermann W, Wolter
J, Pegram M, Baselga J, Norton L (2001) Use of chemotherapy plus a monoclonal antibody against HER2
for metastatic breast cancer that overexpresses HER2. New England Journal of Medicine, 2001 Mar 15;
344(11): 783-792.
25
Taylor C, Hershman D, Shah N, Suciu-Foca N, Petrylak DP, Taub R, Vahdat L, Cheng B, Pegram M,
Knutson KL, Clynes R (2007) Augmented HER-2 specific immunity during treatment with trastuzumab
and chemotherapy. Clinical Cancer Research, 2007 Sep 1; 13(17): 5133-5143. Vose JM, Link BK, Grossbard ML, Czuczman M, Grillo-Lopez A, Gilman P, Lowe A, Kunkel LA,
Fisher RI (2001) Phase II study of rituximab in combination with chop chemotherapy in patients with
previously untreated, aggressive non-Hodgkin's lymphoma. Journal of Clinical Oncology, 2001 Jan 15;
19(2): 389-397.
Walter S, Weinschenk T, Stenzl A, Zdrojowy R, Pluzanska A, Szczylik C, Staehler M, Brugger W,
Dietrich PY, Mendrzyk R, Hilf N, Schoor O, Fritsche J, Mahr A, Maurer D, Vass V, Trautwein C,
Lewandrowski P, Flohr C, Pohla H, Stanczak JJ, Bronte V, Mandruzzato S, Biedermann T, Pawelec G,
Derhovanessian E, et al. (2012) Multipeptide immune response to cancer vaccine IMA901 after single-
dose cyclophosphamide associates with longer patient survival. Nature Medicine, 2012 Aug; 18(8):
1254-1261.
Bivalent Antibody Vaccines
Bi-specific (or bivalent) antibody molecules recognize two different epitopes, one for each
variable region on the antibody molecule. The rationale behind this class of cancer vaccine is that two
functions are better than one (reviewed in: Sedykh et al., 2018; Krishnamurthy and Jimeno, 2018). For
example, a bivalent antibody could recognize and bind a tumor antigen with one arm, while its other arm
recognizes and binds to an antigen on a cytotoxic T-cell. This double-binding brings the cancer cell in
close proximity to the T-cell that kills it. The binding to the T-cell antigen not only physically tethers the
cancer cell and T-cell together, in some cases (depending on the T-cell antigen) it activates the T-cell. A
study directly comparing the activities of mono-specific and bi-specific antibody treatments showed the
latter group generally has higher potency against tumor cells at a lower dosing amount and with lower
costs of production (Molhoj et al., 2007).
A convenient code for referring to bi-specific antibodies uses an “x” to separate the two binding
functions. For example, the best characterized bi-specific antibody is Blinatumomab, where one
antibody arm recognizes CD19 on the surface of B-cells (such as in leukemia), and the other antibody arm
recognizes CD3 (a T-cell activator present on the surface of T-cells). This antibody is conveniently coded
as CD19 x CD3. Other examples of bi-specific antibodies include: CD3 x glioma marker (Nitta et al.,
1990), CD3 x folate receptor (ovarian cancer cells) (Canevari et al., 1995), CD16 x CD30 (Hodgkin’s
disease) (Hartmann et al., 1997), CD319 x CD28 (B-cell lymphomas) (Daniel et al., 1998), CD64 x Fc-
Receptor (B-cell lymphomas) (Honeychurch et al., 2000), CD30 x CD64 (Hodgkin’s lymphoma)
(Borchmann et al., 2002).
Blinatumomab (CD19 x CD3) (also known as AMG-103) was the first bi-specific antibody
approved for use in the U.S. (in 2014), is (Haagen et al., 1992; Bohlen et al., 1993; Haagen et al., 1994;
DeGast et al., 1995; Weiner and DeGast, 1995). An example of Blinatumomab’s spectacular success is
seen in a 2014 clinical trial performed on 9 patients with acute lymphoblastic leukemia (ALL) (Schlegel
et al., 2014). Of the 9 patients, 4 showed complete cancer remission after one cycle of treatment, and 2
more showed complete remission after the second cycle (6 of 9 complete remissions, 67%) (Schlegel et
al., 2014). Targeting CD19 with antibodies is one of the best success stories for cancer vaccines. CD19
is present on early-stage B-cells, but it is lost when B-cells mature to plasma cells, and it is not present on
stem cells or other normal cells in the body, so these latter cells are not targeted. CD19 is an excellent
target for leukemia, because the patient produces large amounts of early-stage B-cells (hopefully
eliminated by the treatment), while the treatment would leave the stem cells and mature plasma cells
26
(lacking CD19) alone to produce needed antibodies to fight infections (Scheuermann and Racila, 1995).
On December 3, 2014, the bi-specific antibody was approved by the FDA for treating acute lymphoblastic
leukemia (ALL) (FDA, 2014).
In non-small cell lung cancers (NSCLCs), mutations in the epidermal growth factor receptor
(EGFR) are often observed and are thought to play a role in promoting tumor growth (Harari, 2004;
Midha et al., 2015). A monoclonal antibody has been developed that targets the EGFR (Cetuximab),
though tumors can acquire resistance to these treatments through several mechanisms (Pao et al., 2005).
One mechanism identified is the over-expression of the EGFR mutant receptor c-Met, which when bound
by its ligand confers resistance (Turke et al., 2010). To overcome this limitation, scientists at Biologics
Research in Pennsylvania have created a bi-specific antibody that antagonistically binds to EGFR and
mutant c-Met, which when administered to human lung cells showed up to 80% tumor growth inhibition
(Grugan et al., 2016). Clinical trials for this bispecific antibody have not yet been reported.
Another example of a bi-specific antibody is Catumaxomab (also called Trion or Removab), the
first bi-specific and tri-functional antibody approved for use in Europe (in 2009). This antibody binds
EpCAM (present on the surface of ascites tumors) and CD3 (present on T-cells), while the Fc fragment
binds macrophages and dendritic cells (Figure-4). Catumaxomab has several methods of killing the
tumor cells, including T-cell mediated lysis, phagocytosis, and cytokine activity (secreted by the
macrophage and dendritic cells.
Figure-4: Diagram of Bispecific Antibody Catumaxomab. This
antibody binds EpCAM (upper left) present on ascites tumors, and CD3
(upper right) present on T-cells, while the Fc fragment binds
macrophage and dendritic cells (lower center). The mode of killing
includes T-cell activation, phagocytosis, and cytokine release. Figure is
from Sedykh et al., 2018.
Example Clinical Trials with Bi-specific Antibodies
Bispecific antibodies have been used since the early 1990’s in a variety of clinical trials against
several types of cancer (Table-II).
Table-II: Example Clinical Trials with Bispecific Antibodies
Targets Cancer Notes Side-Effects Reference
CD3 X CD19
B-cell non-
Hodgkin’s
lymphoma
3 human patients. The results
showed evidence of successful T-
cell activation.
Relatively safe toxicity. De Gast et
al., 1995
27
B-cell chronic
lymphocytic
leukemia (B-
CLL)
Pre-clinical testing showed the
tumor lysis occurs mostly via
CD8+ cytotoxic T-cells, and that
CD19-negative cells (non-
leukemic cells) were not harmed.
CD19-negative cells
(non-leukemic cells)
were not harmed by the
CD8+ T-cells induced
by the antibody vaccine.
Dreier et
al., 2002
B-cell chronic
lymphocytic
leukemia (B-
CLL)
Their data showed a depletion of
lymphoma cells in 22 out of 25
(88%) patient cases, and the
depletion did not require IL-2
supplement.
Löffler et
al., 2003
CD19-positive
B-cell chronic
lymphocytic
leukemia (B-
CLL)
Used video-assisted microscopy
to show that each activated T-cell
eliminated multiple CD19 tumor
cell targets within a 9 hour time
period, and the tumor cell targets
were completely eliminated
within 24 hours using ratios as
low as 1:5.
Hoffmann
et al., 2005
Variety of
cancers
Under identical experimental
conditions, the bispecific
CD19/CD3 format has far
superior activity compared to the
monospecific formats.
Molhol et
al., 2007
Non-Hodgkin’s
lymphoma
Doses of antibody as low as
0.005 milligrams per square
meter body per day led to an
elimination of all target cells in
the blood, and partial and
complete tumor regressions were
observed at 0.015 milligram
doses. At 0.06 milligram doses,
100% of the patients
experienced tumor regression!
Bargou et
al., 2008
Acute
lymphoblastic
leukemia
(ALL)
Phase-II. 16 of 21 patients
showed a successful minimal
residual disease (MRD). 12 of
the 16 responders had been
refractory to previous cancer
treatments, so any improvement
in their condition is a significant
event.
The most frequently
observed side-effects
were grade-3 and 4
lymphopenia, but were
completely reversible.
Topp et al.,
2011
28
Relapsing
acute
lymphoblastic
leukemia
(ALL)
Phase-II long-term follow-up of
the above study. 61% of the 20
patients had a hematologic
relapse-free survival rate. In a
subgroup of 9 patients who
progressed well enough to also
receive an allogeneic
hematopoietic stem cell
transplant, 65% showed
hematologic relapse-free
survival.
Topp et al.,
2012
B-precursor
acute
lymphoblastic
leukemia
(ALL)
Of the 9 patients, 4 achieved
complete remission after their
first cycle of treatment, 2 showed
a complete remission after the
second cycle, and the remaining 3
patients did not respond to the
treatment.
1 patient experienced
grade-3 seizures, and 2
patients experienced
grade-3 cytokine release
syndrome, but those
events were treatable.
Schlegel et
al., 2014
B-precursor
acute
lymphoblastic
leukemia (B-
ALL)
Multicenter Phase-II study. After
two treatments with CD19 x CD3
antibody, 81 of 189 patients
(43%) showed complete cancer
remission.
The most frequent
adverse events were
febrile neutropenia
(25%), neutropenia
(16%), and anemia
(14%). 2% of the
patients showed grade-3
cytokine release
syndrome. 3 deaths due
to sepsis from E. coli
and Candida were
thought to result from
the treatment by
hindering antibody
formation against the
pathogen.
Topp et al.,
2015
CD19 x
CD3
Refractory/
relapsed (r/r)
acute
lymphoblastic
leukemia
(ALL)
65 patients. The complete
remission (CR) rate was 33/65
(51%). Low responses correlated
with initial high leukemia burden
(p = .02), history of prior extra-
medullary disease (EM)
(p = .005), and active EM at the
time of treatment (p = .05). Of
the refractory cases, 41% had
evidence of EM-ALL
progression, and CD19
expression was negative (18%) or
low (23%).
Aldoss et
al., 2017
29
CD3 x
Glioma marker
Malignant
glioma
10 patients treated with
lymphokine-activated killer
(LAK) cells treated in vitro with
bispecific antibody against CD3
(T-cell activator) x anti-glioma
marker, compared to 10 patients
treated with LAKs alone. In the
control group, 9 patients relapsed
(and 8 died within 4 years). In
the antibody-treated group no
patients relapsed (in 18 months),
4 showed tumor regression, and 4
showed tumor eradication.
Nitta et al.,
1990
CD3 x Folate
Receptor
Ovarian
carcinoma
Of the 19 patients evaluated, 3
showed complete responses
(lasting an average of 22
months), 1 showed complete
intraperitoneal response with
progressive disease in the lymph
nodes, 3 showed partial
responses, 7 had stable disease,
and 5 showed progressive
disease.
Canevari et
al., 1995
CD16 x tumor
marker CD30
Refractory
Hodgkin’s
disease
1 patient experienced complete
remission lasting 16 months, one
patient experienced partial
remission lasting 3 months, 3 had
minor responses, and 1 mixed
response.
Side effects were rare,
and consisted of fever,
lymph node pain, and a
rash.
Hartmann
et al., 1997
CD30 x
immune
activator CD64
Refractory
Hodgkin
lymphoma
Phase 1 trial. Of 10 treated
patients, 1 showed complete
remission, 3 partial remissions,
and 4 had stable disease.
The observed side
effects were transient
and mild. The most
serious were
hypotension (4 of 10),
tachycardia (6 of 10),
fatigue (10 of 10), and
fever.
Borchmann
et al., 2002
Transferrin
receptor (TfR)
x
β-secretase
(BACE1)
The team developed two
humanized bispecific antibodies
against the transferrin receptor
(TfR) (to facilitate transcytosis
across the blood brain barrier,
BBB), and against β-secretase
(BACE1) (to lower amyloid-beta
production in the brain). Dosing
primates with anti-TfR/BACE1
allowed the antibodies to cross
the BBB and reduce brain Aβ.
Wu et al.,
2014
EpCAM
(epithelial
EpCAM
positive
Antibody Catumaxomab. 16
patients, several groups of
increasing antibody doses. The
The most common
adverse events were
chills (93.8 %), fever
(87.5 %), and grade ≥3
Mau-
Sørensen et
al., 2015
30
cancer cells) x
CD3
(T cells)
epithelial
cancer
maximum tolerated dose (MTD)
appears to be 7 µg.
increases in liver
enzymes(56.3 %). One
patient at the highest
dose of 10 µg died of
hepatic failure related to
the treatment, leading to
termination of the study.
CD30 x
CD16A (to
recruit NKs)
Heavily
pretreated
relapsed or
refractory
Hodgkin
lymphoma
Antibody AFM13, Phase-I dose-
escalation study, 28 patients.
Doses of 0.01 to 7 mg/kg body
weight. The maximum tolerated
dose was not reached. Three of
26 evaluable patients (11.5%)
achieved partial remission, and
13 patients (50%) achieved stable
disease. AFM13 was also active
in brentuximab vedotin-refractory
patients (CD30). Phase-II
currently underway.
Adverse events were
generally mild to
moderate.
Rothe et al.,
2015
CD20 x
CD3
CD20-positive
human tumors
This study addressed two of the
problems associated with
bispecific antibodies: high cost
and inconvenient
administration. They used a non-
viral DNA vector mini-circle
(MC) to produce a bispecific
antibody CD20 x CD3. The
procedure produced T-cell
mediated killing of multiple
CD20-positive tumor lines in
vitro, and delivery of the DNA to
mouse liver produced an effective
anti-cancer effect in mouse
xenograft models.
Pang et al.,
2017
EGFR x
HER3
KRAS-positive
MAPK-
positive tumors
KRAS-mutant tumors possess
abnormal MAPK pathway
signaling and cell proliferation.
This was a Phase-IB dose-
escalation study of a combination
of Cobimetinib (which blocks
MAPK signaling) and the bi-
specific antibody duligotuzumab
(which inhibits ligand binding to
two types of receptors: EGFR
and human epidermal growth
factor receptor 3 (HER3). 23
patients KRAS-mutant tumors
were enrolled. The best response
was limited to 9 patients (39%)
with stable disease.
The cobimetinib and
duligotuzumab
combination was
associated with
increased toxicity, and
limited efficacy, so the
study did not proceed to
expansion stage and
closed for enrollment.
Lieu et al.,
2017
The studies summarized above in the table illustrate that using bi-specific antibodies is better than
earlier studies with mono-specific antibodies. While the mono-specific therapies showed few complete
31
cancer remissions, the bi-specific therapies frequently showed complete remissions, including: 22 of 25
patients (88%) (Löffler et al., 2003), 3/3 (100%) (Bargou et al., 2008), 12/20 (60%) (Topp et al., 2012),
6/9 (67%) (Schlegel et al., 2014), 81/189 (43%) (Topp et al., 2015), and 33/65 (51%) (Aldoss et al.,
2017). Thus, bispecific antibody treatments are an improvement over earlier antibody versions.
Problems with Bi-Specific Antibodies
Although bi-specific antibodies have shown strong results against cancer that are generally better
than mono-specific antibodies, they are not perfect. Bi-specific antibodies have many of the same
problems associated with mono-specific antibodies: 1) in some cases the treatment causes patient death,
2) some patient tumors become resistant to the treatment, and 3) the vaccines almost always cause side-
effects. The worst adverse effect observed was patient death. For example, one patient died from hepatic
failure caused by administration of an EpCAM x CD3 bispecific antibody treatment, leading to
termination of the entire clinical study (Mau-Sørensen et al., 2015). And in another study, 3 patients died
from E. coli and Candida sepsis caused by treatment with a CD19 x CD3 bispecific antibody that
eliminated B-cells from the patients hindering their ability to make antibodies against the pathogens
(Topp et al., 2015). But patient death was rare, and most patients treated with bispecific antibodies
showed side-effects that were generally mild, transient, and treatable (Borchmann et al., 2002; Topp et al.,
2011). With respect to patient tumors resistant to the treatments, the reason given most often in the
studies was a loss of target antigen expression by the tumor. This antigen loss was quantitated in one
study targeting CD19 in B-cell lineage tumors whose results showed that of the 41% of the non-responder
patients, CD19 expression was absent (18% of the patients) or low (23% of the patients) (Aldoss et al.,
2017). Two other problems encountered with bispecific antibodies include their high cost and their short
half-life in the body. The high cost typically results from the method of antibody production using
expensive cell culture, and the short half-life results from the rapid clearance and degradation of
antibodies passively administered to the body. Both of these latter problems have recently been addressed
using DNAs encoding the antibodies. For example, one study used a non-viral mini-circle DNA to
produce a bispecific antibody against CD20 x CD3. The procedure allowed long-term production of an
antibody that had strong anti-tumor effects in vitro against human cancer cell lines and in vivo in
humanized mouse xenograft models (Pang et al., 2017).
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Antibody-Drug Conjugate Vaccines (ADCs)
In addition to monovalent and bivalent antibody vaccines, the third type of antibody vaccine is
the antibody-drug conjugate (ADC). Simply targeting and attaching an antibody by itself to a cancer
cell antigen does not always kill the cell (Thomas et al., 2016). The attachment does not always attract
sufficient attention from the immune system to remove the tagged tumor. So, scientists have designed
new types of antibody drugs, ADCs, that combine the power of antibodies (to recognize and bind specific
antigens) with cytotoxic drugs (new highly potent drugs that kill cells in very small quantities).
An ADC drug (Figure-5) typically contains an antibody directed against a tumor antigen
connected by a linker to a cytotoxic drug (that kills the cancer cell) (Casi and Neri, 2012; Flygare et al.,
35
2012; Bouchard et al., 2014; Perez et al., 2014; Chiu and Gilliland, 2016; Kraynov et al., 2016). For a
well-designed ADC, the antibody should strongly bind a tumor-specific antigen, the antigen should not be
expressed strongly by normal cells, the linker should not release the cytotoxic drug (cargo) prematurely
into the circulation, and the toxic cargo should be potent enough to kill a cell with only a few molecules.
Figure-5: General Structure of an Antibody-Drug Conjugate. Shown is the
general structure of an ADC, consisting of a “Y”-shaped antibody (brown),
bound to a highly potent cytotoxic drug (green, diagram right) using a linker
(diagram center). Shown in text are the required properties for each component
(Thomas et al., 2016).
Most ADCs are designed to be internalized in the cancer cell. Once the ADC binds to its target
antigen, the cell engulfs the ADC by receptor-mediated endocytosis, and the ADC enters a membrane-
enclosed endocytic vesicle (endosome). This vesicle becomes acidified, which in some cases releases the
cytotoxic drug into the cytoplasm where it kills the cell (Pastan et al., 2006). To make a good ADC, the
antibody should strongly bind the antigen, the antigen should be highly expressed on the tumor cell (not
normal cells), the linker should be stable in the patient’s circulation to avoid releasing the toxin too soon,
and the cargo drug should be highly potent since only a few molecules will enter the cell.
Several types of cytotoxic drugs are used in ADCs, the most commonly used include drugs that:
1) bind DNA (leading to DNA degradation or alkylation) (i.e. calicheamicin and nemorubicin), 2) block
tubulin (inhibiting cancer cell division) (i.e. DM1 and MMAE), or 3) inhibit RNA polymerases (blocking
ancer cell RNA synthesis and gene expression) (Thomas et al., 2016). Usually 2-4 drug molecules are
attached to each antibody at locations that do not hinder interaction with the antigen (Hughes, 2010).
ADCs also have several types of linkers. The antibody can be linked to drug by one of four
methods: 1) disulfide bond formation, 2) glycol-conjugation, 3) protein tags, or 4) amino acid
incorporation (Pastan et al., 2006; Agarwal and Bertozzi, 2015; Thomas et al., 2016). Linkers can be
cleavable (degraded by proteases inside the endocytic vesicle), or non-cleavable (degraded along with the
antibody inside the vesicle) (Doronina et al., 2006; Jain et al., 2015). Cleavable linkers are usually more
stable in the bloodstream (Thomas et al., 2016). Linkers can be placed at antibody variable regions, hinge
regions, constant regions, or any combination (Agarwal and Bertozzi, 2015).
ADC Examples
Two ADCs are currently approved by the FDA: Trastuzumab emtansine (Kadcyla®) and
Brentuximab vedotin (Adcetris®) (Thomas et al., 2016). A third ADC, Gemtuzumab ozogamicin
(Mylotarg®), was initially approved but was later withdrawn (Nelson, 2010; Richwine, 2010). Kadcyla®
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was developed by Genentech to treat HER2-positive metastatic breast cancer in patients resistant to other
treatments (Niculescu-Duvaz, 2010; LoRusso et al., 2011; Lopus, 2011; Verma et al., 2012; Drugs.com,
2013; About Kadcyla, 2017). Kadcyla is composed of an antibody (Trastuzumab, Herceptin) against the
HER2 receptor on the surface of some types of breast cancer cells conjugated to the cytotoxic drug DM1
(Barok et al., 2014; Jain et al., 2015).
Adcetris® is used to treat CD30-positive lympho-proliferative disorders, including Hodgkin
lymphoma (HL) and anaplastic large cell lymphoma (ALCL) (Van de Donk and Dhimolea, 2012;
Brentuximab vedotin, 2016). CD30 often occurs on the surface of cells of these tumor types, but rarely on
normal cells (Küppers and Hansmann, 2005). Adcetris (Figure-6) contains an antibody (Brentuximab or
cAC10) against CD30 conjugated to 3-5 molecules of the drug monomethyl auristatin E (MMAE) using a
cathepsin-cleavable linker (Van de Donk and Dhimolea, 2012).
Figure-6: Structure of the ADC Drug Adcetris. This antibody-drug
conjugate consists of a mouse-human chimeric monoclonal antibody against
CD30 (yellow) linked via a cathepsin-cleavable linker (blue) to 3-5 units of the
cytotoxic drug monomethyl auristatin-E (MMAE) (purple) that strongly binds
tubulin and blocks cell division (Francisco et al., 2003).
More than 40 ADCs are in the clinical trial stages of development (Thomas et al., 2016), and the
future of ADCs seems bright. However, ADCs are not perfect. Sometimes an ADC drug shows strong
pre-clinical data in mice, but this strong performance does not always carry over to the human clinical
trials. In addition, all ADCs produce adverse side-effects (although they appear to be mostly manageable,
and the side-effects pale in comparison to the poor patient prognosis for untreatable cancer). And ADCs
show varying levels of effectiveness. Therefore, it is necessary to continue developing improved ADCs
that are more effective with fewer side-effects.
First-Generation Versus Second-Generation ADCs
Over the years, the design of ADC drugs has improved significantly (Thomas et al., 2016). Early
ADCs contained mouse monoclonal antibodies (mAbs) against the target antigen, but injecting a mouse
antibody into a human patient often stimulated immune rejection (or lowered half-life) of the drug
(Teicher and Chari, 2011). Early ADCs also had short half-lives in the blood, releasing their toxic
payload into the bloodstream instead of the cancer cell. And the cytotoxic payloads (such as doxorubicin,
vinblastine, or methotrexate) were not very potent, requiring the internalization of multiple ADCs per
cell.
Second-generation ADCs contain mouse-human chimera antibodies or fully humanized
antibodies that produce less of an immune rejection in the patients. An example of an ADC with a fully
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human antibody is CDX-011 (Keir and Vahdat, 2012). In addition, ADC linkers have been designed to be
specifically cleaved by proteases or the acidic environment inside the endocytic vesicle, releasing the
toxic cargo only inside the cancer cell. Moreover, newer ADCs use highly potent payloads (such as
Calicheamicin, Maytansine derivatives like DM1, or Auristatins like MMAE) that are far more toxic
(Lopus, 2011). These highly potent drugs have IC50 values in the nano-molar range compared to the
micro-molar range for first-generation drugs, so they have the same cell-killing effectiveness at 1000-fold
lower concentrations.
ADC Clinical Trials
ADC clinical trials have been performed on a variety of target antigens, including some of the
examples shown in Table-III.
Table-III: Example ADC Clinical Trials
Target Antigen ADC Drug Trial Type
References
CD19 ADC SAR-3419
Phase-I Younes et al., 2009 Coiffier et al., 2011
CD22 Inotuzumab ozogamicin CAT-8015
Moxetumomab pasudotox
Phase-I Advani et al., 2010 Kreitman et al., 2012
Phase-II Kantarjian et al., 2012 Wagner-Johnson et al., 2015
CD30 Brentuximab vedotin Adcetris®
Phase-I Seattle Genetics, 2010 Younes et al., 2010 Younes et al., 2013
Phase-II Younes et al., 2012 Pro et al., 2012
CD33 Gemtuzumab ozogamicin, Mylotarg® Phase-II Daver et al., 2016
Phase-III Castaigne et al., 2012 Petersdorf et al., 2013 Hills et al., 2014
Her2 Kadcyla® Trastuzumab emtansine
T-DM1
Phase-I Krop et al., 2010
Phase-II Burris et al., 2011 Perez et al., 2014 Phillips et al., 2014
Phase-III Verma et al., 2012 Krop et al., 2014
gpNMB Glembatumumab vedotin CDX-011
Phase-I Hamid et al., 2010 Bendell et al., 2014
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(formerly CR011-vcMMAE) Phase-II Yardley et al., 2015
Trop-2 Sacituzumab govitecan IMMU-132
Phase-I Starodub et al., 2015 Faltas et al., 2016
EGFR Depatuxizumab Mafodotin (ABT-414) Phase-I Reardon et al., 2017 Gan et al., 2018
DLL3 Rovalpituzumab Phase-I Rudin et al., 2017
The ADC clinical trials performed to date show a wide range of results, from complete remissions
to no response (Sassoon and Blanc, 2013). But some of the trials can be called spectacular successes,
including the 46% complete remissions seen with a CD22-targeting ADC (Kantarjian et al., 2012), and
the 95% complete remission (21 of 22 patients) seen for CD30-targeting Adcetris (Pro et al., 2012). Side-
effects occurred in most trials, but they were relatively mild and treatable, and should be considered a
necessary risk for these recurring untreatable cancers. Neutropenia (low neutrophil count) was almost
always observed, but it was not fatal. Other common side-effects (as with Adcetris) were: Grade 3 or 4
(serious) adverse events of neutropenia (21%), thrombocytopenia (14%), and peripheral sensory
neuropathy (12%) (Pro et al., 2012).
ADC Side-Effects
Most of the clinical trials performed with ADC drugs showed some side-effects caused by the
treatments. Examples of the side-effects are shown in Table-IV:
Table-IV: Example ADC Side-Effects
Trial
Type Reference Summary of Reported Side-Effects
Phase-I Younes et al.,
2009 Occular problems (such as blurred vision), but no other clinically significant
toxicities.
Phase-I Coiffier et al.,
2011 Ocular toxicity, but the incidence (2%) and severity were low. The hematological
toxicity was insignificant.
Phase-I Advani et al.,
2010 Common adverse effects were thrombocytopenia (decrease in platelets) (90% of
patients), asthenia (weakness) (67%), nausea (51%), and neutropenia (decrease in
neutrophils) (51%).
Phase-I Kreitman et al.,
2012 At the doses used, no dose-limiting toxicity was observed. Minor side-effects
(seen in 25-64% of the patients) included: hypo-albuminemia (low serum
albumin), aminotransferase elevations (mild liver damage), edema, headache,
hypotension, nausea, and fatigue.
Phase-II Kantarjian et
al., 2012 The most frequent adverse effects were: fever (41%), hypotension (26%), and
grade 1-2 liver problems (24%). Two patients died within 4 weeks of starting
treatment, but it was not clear whether the deaths resulted from the treatment or
the cancer.
39
Phase-II Wagner-
Johnson et al.,
2015
Common grade 3 or 4 side-effects during the R-INO portion of the treatment
included: thrombocytopenia, lymphopenia, and neutropenia.
Phase-I Younes et al.,
2010 The most common side-effects were fatigue, pyrexia, diarrhea, nausea,
neutropenia and peripheral neuropathy.
Phase-II Younes et al.,
2012 The most common treatment-related adverse effects were peripheral neuropathy,
nausea, fatigue, neutropenia, and diarrhea.
Phase-II Pro et al., 2012 Grade 3 or 4 adverse events included neutropenia (21%), thrombocytopenia
(14%), and peripheral sensory neuropathy (12%)
Phase-I Younes et al.,
2013 Adverse events were generally grade 1 or 2, but occurred in 41% of all patients.
Phase-III Castaigne et al.,
2012 Persistent thrombocytopenia (16%).
Phase-III Petersdorf et
al., 2013 None reported.
Phase-III
Hills et al.,
2014 Doses of Mylotarg at 3 mg/m2 were associated with fewer early deaths than the
higher dose of 6 mg/m2.
Phase-II Daver et al.,
2016 The most frequent side-effects observed were nausea, mucositis, and hemorrhage.
Phase-I Krop et al.,
2010 The most common drug-related adverse events were thrombocytopenia, elevated
transaminases, fatigue, nausea, and anemia. No serious cardiac events that would
have required drug lowering were observed.
Phase-II Burris et al.,
2011 The drug appeared to be well tolerated; the most frequent side-effects were only at
grade-1 or -2 (mild). Observed grade-3 (serious) problems included hypokalemia
(lowered serum potassium levels) (8.9%), thrombocytopenia (8.0%), and fatigue
(4.5%), although these were observed only in a small minority of patients.
Phase-III Verma et al.,
2012 Grade-3 (serious) adverse events decreased from 57% to 41%. Thrombocytopenia
and liver damage were higher with Kadcyla, while diarrhea, nausea, vomiting, and
erythrodysthesia were higher with the chemotherapy.
Phase-
III Krop et al.,
2014 The Kadcyla group showed higher incidence of thrombocytopenia (5% versus
2%), but had lower incidence of neutropenia and diarrhea.
Phase-II Perez et al.,
2014 No major events reported.
Phase-II Phillips et al.,
2014 Tested a combined treatment which caused only mild grade-1 and -2 adverse
events which were treatable.
Phase-I Hamid et al.,
2010 No major events reported.
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Phase-I Bendell et al.,
2014 Initially, the maximum tolerated dose (MTD) was determined to be 1.34 mg/kg
(limited by the patient’s worsening neuropathy), but the MTD was increased to
1.88 mg/kg (their formal Phase-II dose) after eliminating patients with baseline
neuropathy.
Phase-II Yardley et al.,
2015 The ADC drug showed less hematologic toxicity than the chemotherapy, but
produced more rashes, pruritus (itching), neuropathy, and alopecia. The authors
concluded that the ADC was well tolerated.
Phase-
I Starodub et al.,
2015 The MTD was determined to be 12 mg/kg for one cycle of treatment, but that dose
could not be continued for additional cycles due to the formation of
neutropenia. After extended treatments at a lower dose of 10 mg/kg, no level-4
(serious) adverse events were observed, and grade-3 toxicities were fatigue,
neutropenia, diarrhea, and leukopenia.
Phase-I Faltas et al.,
2016 The drug was well tolerated.
Phase-I Rudin et al.,
2016 At a treatment amount of 0.8 mg/kg administered every three weeks, grade 4
thrombocytopenia was observed in two patients. Grade 3 adverse effects that were
noted include thrombocytopenia (11% of individuals), pleural effusion (8%), and
increased lipase (7%). The MTD noted was 0.4 mg/kg every 3 weeks.
Phase-I Reardon et al.,
2017 The most common adverse effects noted were blurred vision, dry eyes, keratitis,
photophobia, and eye pain. MTD was determined to be 2.4 mg/kg.
Phase-I Gan et al., 2018 The most common adverse effects noted were ocular related, occurring in 92% of
patients. Keratitis was the most observed adverse effect. The MTD was
determined to be 1.25 mg/kg.
ADC Problems and Future Directions
Although ADC drugs show great promise, they are not perfect. The continued approval of more
ADC drugs by the FDA will likely require continued improvements in their targeting and efficacy
(Panowski et al., 2014). Thus, there is always room for ADC improvement.
ADC drugs are complex, requiring a number of key steps to be effective. The disruption of any
of these steps can lower the effectiveness of the drug (Loganzo et al., 2016). The ADC must travel
through the circulatory system without losing its toxic cargo. It must bind the tumor cell without
targeting normal cells. It must be internalized into the cell using the correct vesicle which either degrades
the linker or degrades the entire complex, releasing the drug into the cytoplasm. The cytotoxic drug must
correctly localize to the proper cellular compartment (nucleus for DNA damaging agents, microtubules
for tubulin-binding drugs). A response by a tumor cell to alter any of these key steps can lower drug
effectiveness. Thus, there is room for improvement in each of these processes.
For example, in the situation of a tumor cell that has down-regulated the expression of the target
antigen, thus evading the ADC, the treatment strategy could be altered to include a different ADC that
targets a different antigen on the same tumor cell (Loganzo et al., 2015). Or alternatively, if a tumor cell
over time mutates its DNA to where the gene encoding tubulin expresses a product that no longer binds
DM1 or MMAE cytotoxic drugs (Kavallaris, 2010; Gillet and Gottesman, 2010; Holohan et al., 2013),
then perhaps switching to an ADC that kills by a different mechanism would help. And with respect to
41
drug movement from the vesicle into the cytoplasm, in some cases the drug is carried outside the cell by
drug transporter molecules such as MDR1 and MRP1, decreasing drug effectiveness (Chen et al., 2015;
Yu et al., 2015). Perhaps this problem could be overcome by co-treating with a drug to lower MDR1 or
MRP1 expression.
The following topics were identified in our review of the ADC literature as potential future
directions:
1) Cargo Switching: In some cases, a patient’s tumor can become resistant to the cytotoxic drug used in
a therapy, so perhaps switching to a different ADC that targets the same antigen but contains a different
cytotoxic cargo that works by a different mechanism might improve effectiveness. This switching
approach has successfully been used in a mouse model of non-Hodgkin lymphoma (NHL), where altering
the CD22-targeting ADC payload from MMAE (which blocks tubulin polymerization, preventing cell
division) to nemorubicin (which targets DNA) overcame the resistance (Yu et al., 2015).
2) Closely Monitoring Target Antigen Expression: One of the best practices observed in the clinical
trials was the constant monitoring of target antigen expression by the patient’s tumor cells. In some
cases, the tumor down-regulates antigen expression, so any targeted therapy (such as an ADC) no longer
targets those cells. The best clinical response rates were observed for patients still expressing the target
antigen. Antigen expression can be monitored by IHC (immuno-histochemistry), or RT-PCR (reverse
transcriptase polymerase chain reaction).
3) Dual-Targeted Therapies: This approach uses two different ADCs targeting different antigens on the
same tumor. This strategy would allow continued targeting, even in those cases where the tumor cells no
longer express one of the target antigens.
4) New ADC Conjugation Reactions: Chemical conjugation reactions are used to link the antibody to
the drug cargo. Early-generation ADCs used conjugation reactions that could add drug molecules onto
any site on the antibody containing a reactive amino acid (Panowski et al., 2014; Agarwal et al.,
2015). But these reactions added the drugs randomly onto the antibody, producing a heterogeneous
mixture of ADC molecules, each with their own activities. And each production batch varied in
composition, making it difficult to compare clinical trial data (Panowski et al., 2014; Agarwal et al.,
2015). Newer methods of conjugation allow the drug to be added to specific sites, helping eliminate
heterogeneity. The newer methods include the use of engineered cysteine residues, and the use of non-
natural amino acids.
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48
Lit Review Section-2:
Dendritic Cell Vaccines
Leila Camplese
Half of the 2011 Nobel Prize in Physiology or Medicine went to Ralph M. Steinman for his
“discovery of the dendritic cell and its role in adaptive immunity" (Nobel Prize, 2011). As mentioned
previously in the Introduction to Immunology section, dendritic cells (DCs) are “professional” antigen-
presenting cells that reside in tissues that contact the external environment (skin, lining of the respiratory
tract, nasal epithelium, etc.). Their main function is to recognize foreign antigens on the surface of
invading pathogens, process the antigen within the DC, present the antigen on the cell surface, then
migrate to the lymph nodes to present the antigen to other cells of the immune system (T-cells and B-
cells) (Steinman and Cohn, 1973; Banchereau and Steinman, 1998; Sallusto and Lanzavecchia, 2002;
Trombetta and Mellman, 2005). These latter immune cells then differentiate and commit to that antigen
to help eliminate the threat.
In the case of cancer, the tumor cells themselves are poor antigen-presenting cells, so DCs help
facilitate the tumor removal by presenting their antigens to the immune system to induce a response to the
tumor. Animal experiments have shown that DCs are a required component of the body’s immune attack
against cancer. When a tumor forms in the body, DCs help process the tumor’s neo-antigens and present
them to the immune system to generate active B-cell and T-cell responses against the tumor (Palucka and
Banchereau, 2012).
With respect to tumor vaccines, the antigen-presenting properties of DCs are sometimes used to
“prime” a patient’s DCs against a single antigen, or mixture of antigens (Figure-7). In a common ex vivo
approach, a patient’s DC cells are isolated from peripheral blood mononuclear cells (PBMCs) using
various techniques, and are cultured to expand their numbers. The isolated DCs are then “pulsed” or
“primed” (mixed) with foreign tumor antigen (purified antigen or entire tumor cells themselves) (dagram
upper left), and the pulsed DCs are injected back into the patient. Hopefully, these primed DCs migrate
to the lymph nodes to engage B-cells and T-cells (diagram right) to commit them against the tumor
antigen (Davis et al., 2003; Steinman and Banchereau, 2007; Koski et al., 2008; Schuler, 2010; Ueno et
al., 2010). In a less used in vivo approach, DCs in the patient’s body are induced to take up tumor-specific
antigens, and the antigen-presentation is done naturally to stimulate the patient’s T-cells. This latter
process does not involve purification of the DCs nor their ex vivo expansion.
Figure-7: Diagram of a Typical DC Vaccine. In this
approach, dendritic cells (DCs) (purple) are primed with tumor
antigens (diagram upper left). The priming can be performed in
vitro or in vivo. The activated DC cells migrate to nearby
lymph nodes and present the antigens bound to MHCs (light
brown). MHC-I presents to T-cell receptors (blue) on CD8+
cells (yellow), while MHC-II presents to T-cell receptors on
CD4+ cells (also yellow). CD4+ helper T-cells produce
cytokines that promote CD8+ T-cell maturation. CD8+
cytotoxic T-cells leave the lymph node into the circulation
where they recognize the tumor cells expressing the antigen,
killing the cell. Figure from Anagnostou and Brahmer, 2015.
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Example Studies with DC Vaccines
The first DC vaccine approved by the FDA was Provenge (Ledford, 2015). This vaccine is also
called Sipuleucel-T or APC8015. Provenge is directed against prostate cancer, the second leading cause
of cancer death in men following skin cancer. Researchers chose prostate cancer, because so many men
have it, and also because men can live without a prostate so if the vaccine accidently targeted normal
prostate cells it would not be fatal (Ledford, 2015).
Much research went into the development of this vaccine. A patient’s peripheral blood
mononuclear cells (PBMCs) (including DCs) are isolated by leukapheresis, and cultured to increase their
numbers. They are then mixed in vitro with a patented recombinant fusion protein (PA-2024). PA-2024
used to prime the DCs contains the target antigen prostatic acid phosphatase (PAP) fused with
granulocyte macrophage colony stimulating factor (GM-CSF) which helps activate the immune system.
The primed DCs are then injected back into the same patient.
The clinical results of Provenge (Table-V) are mixed, showing some successes, followed by an
underwhelming response. Early experiments demonstrated that CTLs had been formed against the tumor
cells, and that PSA levels dropped, but the survival statistics were relatively unimpressive compared to
controls, for example increasing from 4.9 months survival before treatment to 7.9 months after treatment
(Beinart et al., 2005), but few of the clinical trials showed complete remissions. Despite Provenge’s FDA
approval, the company who developed it (Dendreon Corp.) went bankrupt. Dendreon was hurt by the
long wait for FDA approval for an early cancer vaccine (18 years), by confusion over Medicare
reimbursements, and by lukewarm results (Ledford, 2015). In 2015, the rights to Provenge were
purchased by Valeant Pharmaceuticals.
As with any clinical treatment, there are several risks associated with Provenge. Many of them
are clearly listed on their website as acute infusion reactions, including (but not limited to): fever,
headache, nausea, and joint pain (Dendreon Pharmaceuticals, 2017). More rarely the patients can
experience more severe side-effects, such as chest pain, vomiting, stroke, and thrombosis. 1.5% of the
participating patients backed out of the clinical trial upon experiencing these side effects, however this
number is so low that it would not have a significant impact on the study results (Dendreon
Pharmaceuticals, 2017).
Melanoma is another cancer treated with DC vaccines. In these cases, the patient’s DC cells were
either pulsed with tumor lysate or were pulsed with a mixture of melanoma peptides identified from
animal studies. Some of the melanoma trials produced stronger data than obtained with Provenge. DC
vaccines have also been used to treat glioblastomas (GBMs), a particularly devastating cancer with a
median survival time of less than 2 years (Johnson and O’Neill, 2012). Table-V below shows examples
of experiments with DC vaccines.
Table-V: Example Experiments with DC Vaccines
Cancer Notes Side-Effects Reference
Prostate Cancer Phase-I study. Autologous DCs pulsed with
HLA-A0201-specific prostate-specific
membrane antigen (PSMA) peptides. A
decrease in PSA was observed only in the
group receiving DCs pulsed with peptide P2.
No significant toxicity was
observed for any of the
treatment groups.
Murphy et
al., 1996
50
Melanoma Phase-I. Regression of metastases was
observed in 5 of the 16 patients. The vaccinations appeared to
be well tolerated, and did not
generate any visible
autoimmune responses.
Nestle et al.,
1998
Prostate Cancer Phase-I/II. 100% of the patients showed an
immune response against the priming PA-
2024.
The most common side-
effect observed was fever
(14.7% of the patients).
Small et al.,
2000
Prostate Cancer Phase-I. Circulating levels of PSA dropped in 3
of the 13 treated patients. The patients experienced
mild grade-1 and -2 side
effects, such as fever, chills,
myalgia, pain, and fatigue.
Burch et al.,
2000
Melanoma Phase-I. 2 of the 14 patients showed anti-tumor
responses, including regression of metastasis. 1 patient developed vitiligo,
but that skin discoloration
was minor and treatable.
Mackensen
et al., 2000
Melanoma Phase-I. 9 of 12 patients developed CTLs
capable of destroying melanoma cells. The vaccine seemed to be
well tolerated, except 2
patients showed progressive
vitiligo (skin discoloring)
Banchereau
et al., 2001
Glioblastoma Phase-I. 4 out of 7 evaluated patients showed
sustained anti-tumor CTL responses. Median
survival time of the DC group was 455 days
compared to 257 days for the control group.
No serious side effects were
seen. Yu et al.,
2001
Prostate Cancer Phase-II. 2 of the 21 patients showed a 25-50%
drop in PSA levels. One patient dropped PSA
to undetectable levels and resolved his cancer.
Most of the side-effects were
grade-1 and -2, with only 4
of the 21 patients showing
grade-3 or 4 side-effects.
Burch et al.,
2004
Glioblastoma Phase-I. The DCs were primed with tumor
lysates from the same patient. 6 of 10
evaluated patients showed robust T-cell
responses against the tumors.
The vaccines appeared to be
well-tolerated, and no
evidence of autoimmune
disease was seen.
Yu et al.,
2004
Glioblastoma Phase-I. 1 out of 12 patients showed a clinical
response (improved MRI). 6 had measurable
anti-tumor CTL responses, but those did not
translate into clinical responses or prolong
patient survival.
Liau, et al.,
2005
Prostate Cancer Phase-II. 13 of the 18 patients slowed the rate
of increase of their serum PSA levels. None noted. Beinart et al.,
2005
Melanoma Phase-I. 67% of the patients showed CD8+
cells reactive against the priming peptide
G280, and 9 of 9 patients tested had T-cells
that were able to lyse tumor cells in vitro. 3 of
the 9 patients tested showed stable disease, and
2 showed partially stable disease.
None reported. Linette et al.,
2005
51
Melanoma Phase-I. 11 of the 15 showed enhancement of
immune responses against the target antigens.
2 out of 9 evaluable patients showed clinical
responses, one showed complete cancer
regression, the other one showed disease
stabilization.
Salcedo et
al., 2006
Prostate Cancer Phase-III. 147 patients treated with Provenge,
and 78 placebo. Found an average 33%
reduction in death for the patients receiving
Provenge versus the placebo (p=0.011).
The most common Provenge-
induced side-effects were all
grade-1 or 2 (mild), lasting
only 1-2 days. They
included: chills, pyrexia
(fever), headache, asthenia
(weakness), dyspnea (labored
breathing), vomiting, and
tremor.
Higano et al.,
2009
Melanoma Review. 626 patients. Improved clinical
responses correlated with the use of peptide
antigens to pulse the DC cells (p=0.03), the use
of adjuvant (p=0.002), and the induction of
antigen-specific T-cells (p=0.0004)
Engell- Noerregaard et al., 2009
Prostate Cancer Phase-III. 341 patients treated with Provenge,
and 171 placebo. Double-blind, placebo
controlled, multicenter trial. Provenge patients
had an average 22% reduction of death, with
survival extending from 21.7 months to 25.8
months.
Adverse effects included
chills, fever, and headache. Kantoff et
al., 2010
Prostate Cancer Summary of 17 Provenge trials. Stable disease
was observed in 54% of the Provenge patients.
High DC doses significantly correlated with
clinical benefit.
Draube et al.,
2011
Melanoma Phase-I. Compared intra-nodal and intra-
dermal vaccinations. All of the intradermal
vaccinated patients showed beneficial DC
migration to the nodes, compared to no
migration for 7 of 24 intra-nodal patients.
Lesterhuis et
al., 2011
Glioblastoma Phase-I. 23 patients with grade-4 GBM were
vaccinated with tumor lysate-pulsed DCs
accompanied by adjuvant. The vaccines
produced a median survival time of 31.4
months, compared to less than 24 in controls.
The vaccines appeared to be
well tolerated. Prins et al.,
2011
Glioblastoma Phase-I. This was the first study to treat
recurrent human malignant gliomas with a
combination of αDC1 cells and adjuvant. Of 19
evaluable patients, 58% had positive immune
responses against the target antigen. 9 patients
had no sign of tumor progression for at least 12
months, and 1 patient showed sustained
complete remission.
The vaccines were well-
tolerated. Okada et al.,
2011
52
Melanoma Phase-I. 6 of the 7 patients showed sustained
anti-tumor T-cell responses. 1 patient showed
complete remission, and 2 showed partial
remission. Strong improvements correlated
with with DC cells producing IL-12, and for
patients with strong T-cell responses.
Carreno et
al., 2013
Glioblastoma Pre-Clinical. Pulsing DC cells with glioma
stem cell lysate (these cells often re-seed the
tumor) better forms anti-tumor T-cell
responses than non-stem cell primed DCs.
Ji et al., 2013
Melanoma Phase-I. Used new exome sequencing
technologies to identify neo-antigens present
in the tumor cells, not normal cells. Bio-
informatics was used to identify missense
mutations likely to produce neoantigens. They
selected about 7 neo-antigens per patient,
synthesized them chemically, then charged the
DC cells. T-cell responses were generated
against some, but not all 7 of the neoantigens,
indicating they are not equal in their ability to
induce an immune response.
Carreno et
al., 2015
Glioblastoma Phase-I. Patients were vaccinated with DCs
primed against cytomegalovirus
phosphoprotein-65. Patients also receiving an
adjuvant of tetanus toxoid Td (to generally
boost the immune system) showed a greater
DC migration to the desired location (vascular
draining lymph nodes) than patients without
adjuvant.
Mitchell et
al., 2015
Metastatic
Melanoma Melanoma patients sometimes develop
resistance to immunotherapies via an immune
suppressive tumor microenvironment. Here,
the authors demonstrated in mouse models that
macrophages (MOs) and dendritic cells (DCs)
are suppressed in metastatic melanoma, and
that peptide C36L1 can restore MO and DC
function, including inhibiting metastatic
growth in lungs. The C36L1 treatment
activates MOs, increase the immunogenic DCs,
increase activated cytotoxic T-cells, and reduce
the number of regulatory T-cells in metastatic
lungs. The C36L1 peptide directly binds
receptor CD74 on MOs and DCs, inhibiting
MIF signaling.
Figueiredo et
al., 2018
Colon
Carcionma In this study, the authors investigated the use
of stereotactic body radiation therapy (SBRT)
as a method for facilitating the presentation of
tumor-associated antigens (TAA) to immature
dendritic cells (iDCs). They tested their
method on mouse xenograft models of CT-26
colon carcinoma with 3 groups of mice: 1)
radiation therapy alone (RT), 2) intra-tumor
Choi et al.,
2018
53
injection of DCs electroporated with tumor
antigens (DC), or 3) the combination
(RT/iDC). The data showed that the radiation
method achieved the best DC priming and T-
cell activation compared to other priming
methods, and that mouse survival was highest
in the combination treatment group. The
authors conclude that clinical trials are
warranted.
Glioblastoma Phase-III trial of 331 patients with
glioblastoma. The standard therapy for
glioblastoma includes surgery, radiotherapy,
and oral chemotherapy temozolomide. This
study evaluated the addition of an autologous
tumor lysate-pulsed dendritic cell vaccine
(DCVax®-L) to standard therapy for newly
diagnosed glioblastoma patients. After surgery
and chemo-radiotherapy, patients were
randomly assigned to two groups: 1) chemo +
DC vaccine (232 patients), or 2) chemo +
placebo (99 patients). But if the cancer
recurred, the patients were allowed to receive
the DC vaccine. Due to this cross-over design,
nearly 90% of the patients received the DC
vaccine, so patient survival relative to a
placebo could not be determined. However,
median overall survival 34.7 months, with a 3-
year survival of 46.4%.
Only 2.1% (n = 7) of the
patients had a grade 3 or 4
adverse event that was
deemed at least possibly
related to the vaccine.
Overall adverse events with
DC vaccine were comparable
to standard therapy alone.
Liau et al.,
2018
Lewis lung
carcinoma and
breast cancer
cells
In some cases, the tumor microenvironment
can inhibit the activation of the immune system
to fight a tumor, including antigen-pulsed DC
cells. The authors developed a system to
determine whether exosomes (membrane
vesicles) produced by LLC Lewis lung
carcinoma or 4T1 breast cancer cells contribute
to DC immune suppression. They found that
exosomes from these tumors blocked the
differentiation of myeloid precursor cells into
DC cells, and inhibited the migration and
maturation of DCs. The inhibitory response
was partially blocked by treating with anti-PD-
L1 antibody, suggesting this checkpoint
inhibition was important to the inhibition.
Ning et al.,
2018
Diffuse
Instinsic
Pontine Glioma
Phase-Ib clinical trial of 9 patients with diffuse
intrinsic pontine glioma (DIPG), a lethal
brainstem tumor in children. They tested
autologous dendritic cell vaccines (ADCVs)
pulsed with an allogeneic tumor cell-line
lysates in newly diagnosed patients following
radiation therapy. The DCs were prepared
from monocytes obtained by leukapheresis.
The authors found that their procedure boosted
non-specific (KLH) (9/9 patients) and specific
glioma immune anti-tumor responses (8 of 9
The DC vaccine
administration was safe in all
treated patients.
Benitez-
Ribas et al.,
2018
54
patients) in PBMCs and in T-lymphocytes
isolated from CSF.
Glioblastoma Glioblastoma (GBM) tumors strongly suppress
the immune system. Checkpoint blockage
vaccines (such as antibodies against PD-1)
might be useful for overcoming the blockade,
but some experiments suggest the checkpoint
approach may not be sufficient. This team
investigated the activation of DC cells as a
supplement to anti-PD-1 therapy in mice.
Their data shows that activating DCs (by
stimulating the TLR3 receptor with poly(I:C)
enhances the PD-1 anti-tumor response and
increases survival in mouse models of
glioblastoma. DC depletion experiments
showed that DCs are required for the anti-
tumor response. The authors conclude that
increasing DC antigen presentation is
important to the anti-tumor response, and that
multi-modal immunotherapy strategies are
important.
Garzon-
Muvdi et al.,
2018
Metastatic
breast cancer The authors investigated the use of
chemotherapy agent Dasatinib as a supplement
for a DC vaccine against metastatic breast
cancer in mice. Their data showed that tumor
volume deceased in the group receiving the
combined treatment, but not in groups
receiving single vaccines. Mouse survival was
longest in the combined treatment group.
Song et al.,
2018
DC Vaccine Future Directions
Overall, while some scientists argue that DC clinical trials have produced somewhat modest
results so far, the data suggests some potential ways for improving efficacy: 1) Adjuvants: Some trials showed improved outcomes combining DCs with adjuvants such as poly(I:C)
(Okada et al., 2011; Ammi et al., 2015), or with IL-12 hormone to boost the immune response (Carreno et
al., 2013), or tetanus toxoid Td (Mitchell et al., 2015). For example, in the latter study, glioblastoma
patients were pretreated at the site of the injection with a recall antigen (in this case, tetanus/diphtheria
(Td) toxoid) with the intention of increasing the efficacy of tumor antigen-specific dendritic cells. Out of
thirteen patients, all of them showed greater accumulation of DCs when given Td than those who were
not pretreated. Three of these patients’ glioblastomas halted progression and had extended survival time.
The overall results of this study concluded that patients given a recall antigen pretreatment had generally
increased survival times compared to patients treated with DCs alone (Mitchell et al., 2015). With further
research, application of adjuvants under different types of circumstances may lead to significantly
improved results.
55
2) Tumor Heterogeneity: Some experiments have shown that tumors are not homogenous, but instead
are composed of different types of cells each expressing different neo-antigens. Each type of tumor cell is
genetically distinct from its neighbors, meaning they are different regarding growth rates, metabolic
pathways, and overall aggression, among other characteristics. Perhaps most importantly, certain types of
cells may develop immunity to treatments while others do not. This situation would require several levels
of treatment and decrease the chance that growth will be suppressed or that the tumor will regress on its
own. In these cases, targeting only one antigen would not kill all the tumor cells, so perhaps targeting
multiple antigens would improve efficacy. 3) Which DCs: DC cells are not all alike. Isolating DCs on the basis of surface antigen CD14 selects for
immature cells, but it is not clear whether priming mature or immature DCs is most efficient. Expanding
DCs with hormone Flt3L appears to enrich for a more mature population. Other investigators have had
success using αDC1 cells (Andrews et al., 2008; Okada et al., 2011).
4) Patient Selection: Some patients respond better to DC vaccines than others, but it is not clear
why. Experiments should be done on the tumor micro-environments from various patients to determine if
differences there block immune responses in some patients. For example, the amount of TGF-beta
present in the tumor can strongly affect the immune response (Derynck et al., 2001). 5) Combination Vaccines: To further improve vaccine efficacy, perhaps combinations of cancer
vaccines could be tested, such as combining DC vaccines plus an immune checkpoint vaccine against
CTLA. A clinical study was done to test this mechanism in 16 patients suffering from metastatic
melanoma. The patients were administered the DC vaccine along with a dose of cytotoxic T lymphocyte-
associated antigen 4 (CTLA4)-blocking antibodies. The purpose of adding the antibodies is that they
provide a negative-feedback response to the body’s immune system to promote the activation of T
lymphocytes. The results of this study showed that four patients were entirely tumor-free within two to
four years after the start of the treatment, with no observable relapse. One patient also had total lung
metastasis regression after 4 months, as well as significant (55%) regression of a spinal mass. This
suggests that the combination of both treatments has a better overall result than that of each treatment
individually (Ribas et al., 2009). Other example combination vaccines are Garzon-Muvd et al., 2018 and
Song et al., 2018.
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Lit Review Section-3:
TIL Cancer Vaccines
Michaela Hunter
In addition to cancer vaccines that use therapeutic antibodies or dendritic cells (the topics of
previous sections), T-cells are also used as cancer vaccines. T-cells are a type of nucleated white blood
cell that matures in the thymus (thus their name) (although some T-cells also mature in the tonsils)
(Zhang and Bevan, 2011). There are several types of T-cells, including: helper (CD4+), cytotoxic (CD8+),
memory, suppressor, mucosal associated, and gamma delta T-cells.
With respect to cancer vaccines, tumor infiltrating lymphocytes (TILs) are a mixture of T-cells
that locate and infiltrate a tumor to help kill it. TILs isolated from patient tumors include CD4+ (helper T-
cells) and CD8+ cells (cytotoxic T-lymphocytes, CTLs). The CD4+ cells secrete cytokines to activate the
immune system, while the CTLs directly lyse the tumor cell. High levels of TILs in tumors are often
associated with a better clinical outcome (Vanky et al., 1986). T-cell therapy is sometimes referred to as
adoptive cell therapy (ACT) because T-cells are isolated from a patient, expanded in vitro, selected for
particular T-cells targeting a specific antigen, and perfused back (adopted) into the same patient
(reviewed in: Rosenberg and Restifo, 2015; Mayor et al., 2018; Saint-Jean et al., 2018). So, TIL or ACT
therapy is a form of personalized medicine.
So far, TIL therapy can only be performed in a few large medical centers due to the highly
specialized patient care required and the complexity of TIL culture. After isolation of a patient’s TILs,
and before their re-perfusion, the patient is often treated with high-doses of chemotherapy to deplete any
remaining lymphocytes that could block the therapy. And sometimes interleukin-2 (IL-2) injections are
given to increase survival of the perfused T-cells. One advantage of using TILs to fight cancer is that the
in vitro expansion process can sometimes avoid the negative regulation T-cells encounter near the tumor
site by checkpoint inhibition via PD-1, PD-L1, or CTLA-4 (discussed in a later section). So, the ability to
grow and expand T-cells in vitro has been a major advance in the field of cancer therapy.
Examples of TILs and Cancer
Dr. Steven Rosenberg at the National Cancer Institute pioneered the use of TILs to fight cancer,
especially melanomas (for a review, see Rosenberg and Dudley, 2009). His lab helped develop the
procedures for isolating a patient’s TILs and amplifying them in vitro. He also helped develop the
procedure of chemoablation, the use of chemotherapy to deplete a patient’s in vivo lymphocytes that can
suppress TIL function, and then afterwards re-perfusing the therapeutic TILs into the patient. The TIL
studies published so far on melanomas show an impressive clinical response rate of up to 50% with no
side-effects, including a significant proportion of patients with durable complete response (Mayor et al.,
2018). In addition to melanomas, TILs have also been used to fight epithelial and ovarian cancers. Table-
VI below shows some example studies of treating cancer with TILs.
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Table-VI: Example Studies Treating Cancer with TILs
Cancer Type Notes Side-Effects Reference
Metastatic
melanoma 9 of the 41 patients (22%) achieved complete or partial
cancer remissions. Positive outcomes correlated with
high TIL numbers.
Schwartzentruber et
al., 1994 Rosenberg’s team
Metastatic
melanoma Phase-I study, 10 patients. TILs were isolated against
antigens MART1 and gp100 targets. The T-cells
persisted in vivo at least 21 months (using supplement
IL-2) and localized to tumor sites.
No serious
toxicity was
observed.
Yee et al., 2002
Metastatic
melanoma 13 patients. All received chemoablation in advance
and high dose IL2 therapy. 6 of 13 patients (46%)
showed significant tumor regression.
Dudley et al., 2002 Rosenberg’s team
Metastatic
melanoma 2 of the 15 patients showed high levels of circulating
TILs one year after injection, and observable tumor
regression.
Morgan et al., 2006 Rosenberg’s team
Metastatic
Melanoma Patients received pre-treatment chemoablation and/or
total body irradiation, followed by TILs. 49% of the
patients receiving the TILs and no irradiation had an
objective response. Adding 2 Gy irradiation increased
the response to 52%, and adding 12 Gy increased the
response rate to 72%.
Dudley et al., 2008 Rosenberg’s team
Metastatic
melanoma 20 patients received chemoablation and TILs. 50% of
the patients achieved an objective clinical response: 2
complete remissions, and 8 partial remissions.
Manageable
toxicity. Besser et al., 2010
Metastatic
melanoma 93 patients, pre-treated with chemoablation and
radiation. 20 of the 93 patients (22%) achieved
complete tumor regression, and 19 of the 20
regressions remained negative for at least 3 years! The
3 and 5-year survival rates for the 20 remission patients
were 100% and 93%, respectively.
Rosenberg et al.,
2011
Metastatic
melanoma 31 patients. Each received chemoablation and IL-2. 15
of the 31 (48.3%) showed an objective clinical
response.
Radvanyi et al.,
2012
Metastatic
melanoma 19 patients, but only 13 completed the
treatments. Each received chemoablation and IL2. 2 of
13 had complete responses, and 3 had partial responses.
In addition, 4 patients had stable disease.
Pilon-Thomas et al.,
2012
Metastatic
melanoma 69 patients, 35 receiving TILs with no selection and 35
enriched for CD8+ CTLs. 12 patients receiving the
unselected TILs responded to the therapy, while only 7
responded to the CD8+-enriched TILs, so the CD8
enrichment may not be worth the effort.
Dudley et al., 2013 Rosenberg’s team
62
Metastatic
melanoma Used whole-exome DNA sequencing of tumor DNA
followed by bioinformatics to identify potential
neoantigens. They synthesized the neo-antigens
synthetically, and tested their recognition by patient
TILs. They identified neoantigens present in about
40% of long-term (5-years) survival patients.
Robbins et al., 2013 Rosenberg’s team
Ovarian cancer Designed a new digital DNA-based assay (termed
QuanTILfy) to count TIL cells and assess their
clonality (percent activity against various antigens).
They demonstrated an association between higher
patient TIL counts and improved patient survival
Robins et al., 2013 Bielas’ team at the
Fred Hutchinson
Metastatic
melanoma Used deep sequencing techniques to determine which
cancer antigens the TIL cells recognized and whether
any TILs expressed inhibitory receptors. Their data
indicated that 6 of 6 analyzed tumors contained TILs
positive for mutated neo-antigens, and all 6 contained
TILs positive for negative immune receptors PD-1,
LAG-3, and TIM-3, indicating that the TILs in their in
vivo state were functionally impaired by the
tumor. Thus, antibody therapy designed against the
negative regulators might improve vaccine
effectiveness.
Gros et al., 2014 Rosenberg’s team
Epithelial
cancer Performed whole exome sequencing on TILs isolated
from epithelial tumors, and showed the TILs
specifically reacted against erbb2-interacting protein
(erbb2ip). When treated with a TIL cell population
where 25% were specific for erbb2ip, the patient
showed a decrease in lesions and disease stabilization.
Tran et al., 2014 Rosenberg’s team
Inflammatory
breast cancer
(IBC)
The authors measured the levels of proteins PD-L1
(checkpoint inhibitor) and CD20 (tumor marker) in 221
biopsies as potential biomarkers of patient
outcomes. The presence of high levels of CD20+ TILs
plus high levels of PD-L1+ TILs was an independent
prognostic factor for patient disease free survival. The
authors suggest pursuing the use of anti-PD-1 or anti-
PD-L1 therapies in these patients.
Arias-Pulido et al.,
2018
Advanced
Melanoma TILs were expanded from excised cutaneous or
subcutaneous metastases and then infused into the
patients who also received subcutaneous IL-2. 9
patients were treated (4 had stage-IIIC melanoma, and
6 had stage-IV melanoma). All but 1 patient had
previously received at least 2 other treatments. The
results showed 1 complete remission, 1 partial
remission, 2 stabilizations, and 6 cancer progressions.
No serious
adverse effects
were reported.
Saint-Jean et al.,
2018
Colorectal
Cancer (CRC) The purpose of the study was to help standardize the
method of evaluating TILs in colorectal cancer (CRC)
clinical trials, as the methods currently differ in each
study. They analyzed 160 patients with Stage II or III
CRC using a new method proposed by the International
TILs Working Group in breast cancer that measured
Iseki et al., 2018
63
the area occupied by mononuclear cells over the
stromal area on H&E stained sections. They classified
patients into high-TIL density and low-TIL density
groups. Their results showed that the rates of relapse-
free survival (RFS) and overall survival (OS) in the
high-TILs group were significantly higher than those in
the low-TILs group.
Advanced
Breast Cancer The authors investigated whether the TIL scores taken
from core needle biopsies (CNBs) represent those
taken from resected specimens. They analyzed 220
matched pairs of CNBs and resected specimens,
scoring stromal TILs on slides stained with H&E. The
authors concluded that more than five CNB cores may
accurately predict the TIL score of the entire tumor.
Cha et al., 2018
Metastatic
Urothelial Carcinoma
The authors investigated the prognostic role of TIL
levels on survival in patients with metastatic urothelial
carcinoma (mUC) receiving platinum based
chemotherapy. They analyzed 259 mUC patients, of
which 179 (69%) had intense TILs, and 80 (31%) had
non-intense TILs. The median overall survival was
15.7 months for the intense TIL group versus 6.7
months for the non-intense group (p < 0.001). The
authors conclude that assaying TIL staining intensity
(numbers) for mUC patients is clinically useful for
patient risk stratification and counseling.
Huang et al., 2018
TIL Problems and Future Directions
The data with TIL therapy shows great promise. In some cases, the teams observed 50% tumor
reduction in about half the patients (Dudley et al., 2008; Besser et al., 2010; Radvanyi et al., 2012; Pilon-
Thomas et al., 2012), and in another study, 22% of the melanoma patients showed complete cancer
remission even 3 years post-treatment (Rosenberg et al., 2011). Some studies noted a direct correlation
between high TIL load and positive patient outcomes (Iseki et al., 2018; Huang et al., 2018), so future
research should focus on methods for further amplifying the cells. And due to poor patient prognosis, the
amplification process needs to be done quickly, so methods to speed amplification are important. In the
case of ovarian tumors, they presented a large variety of neo-antigens, so future experiments should
determine whether amplifying TILs targeting one neo-antigen is sufficient in these cases. In some cases,
the patient’s tumor is found to have very low or no detectable TILs, so future research should also focus
on devising new methods for detecting rare TILs. Immune checkpoint inhibitors can sometimes be a
problem with TILs. One study noted a high expression of negative regulator receptors PD-1, LAG-3, and
TIM-3 on the isolated TILs, so some tumors may be expressing ligands that engage these inhibitory
receptors inactivating the TILs. Future tests should be done with combination treatments of TIL cells
plus an antibody against one of these inhibitory receptors.
Cited TIL References
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Prossnitz ER, Emens LA, Fiering S (2018) The combined presence of CD20 + B cells and PD-
64
L1 + tumor-infiltrating lymphocytes in inflammatory breast cancer is prognostic of improved patient
outcome. Breast Cancer Research and Treatment, 2018 June 1. doi: 10.1007/s10549-018-4834-7.
Besser MJ, Shapira-Frommer R, Treves AJ, Zippel D, Itzhaki O, Hershkovitz L, Levy D, Kubi A, Hovav
E, Chermoshniuk N, Shalmon B, Hardan I, Catane R, Markel G, Apter S, Ben-Nun A, Kuchuk I, Shimoni
A, Nagler A, Schachter J (2010) Clinical responses in a phase II study using adoptive transfer of short-
term cultured tumor infiltration lymphocytes in metastatic melanoma patients. Clinical Cancer Research,
2010 May 1; 16(9): 2646-2655.
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Lit Review Section-4:
CAR Cancer Vaccines
Talal Hamza
In addition to therapeutic antibody vaccines, DC vaccines, and TIL vaccines, are chimeric
antigen receptor vaccines (CARs). CARs, also known as chimeric T-cell receptors, or chimeric
immune-receptors, are a different type of T-cell vaccine than TILs in that the T-cells contain a genetically
engineered T-cell receptor that confers at least two key properties to the T-cells: 1) binding affinity for
the tumor, and 2) signaling properties to activate the T-cells to destroy the tumor (reviewed in: Pule et al.,
2003; Lipowska-Bhalla et al., 2012; Curran et al., 2012; Lim and June, 2017; June et al., 2018; June and
Sadelain, 2018). In this approach, an engineered CAR gene is delivered inside the patient’s own T-cells
in vitro using retroviral vectors, the CAR is expressed on the cell surface, and the engineered T-cells are
delivered back into the same patient. CARs are typically engineered to have a monoclonal antibody-like
affinity for a specific tumor antigen, so they do not rely on formal antigen presentation to recognize the
antigen.
CAR structures have evolved over the years, and are based on the T-cell receptor (TCR) (Figure-
8). The TCR (left panel) consists of extracellular alpha and beta domains associated with CD3
subunits. The T-cell becomes activated when the external TCR domains bind peptides presented by MHC
on the surface of antigen presenting cells or tumor cells. The binding activates signalling via an
intracellular CD3-zeta domain (red). Early CARs (second panel) consisted of antibody-like antigen-
binding domains (antibody variable domains, turquoise), a hydrophobic transmembrane domain, and one
intracellular CD3-zeta signaling domain (red) that becomes activated once the receptor engages the target
antigen. Later generation CARs (third and fourth panels) added additional “co-stimulatory domains”
(such as CD28 or 4-1BB) to help the T-cell divide in vivo. Thus, structurally, CARs combine the
powerful properties of highly specific target antigen recognition (the antibody-like portion), co-
stimulation to increase T-cell survival, and T-cell signaling activation to kill the cancer cell, all combined
in a single engineered receptor molecule (Sadelain et al., 2009).
Figure-8: The Evolution of CAR Structures. Shown are the structures of a typical T-
cell receptor (TCR) (left panel), first-generation (second panel), second-generation (third
panel), and third-generation (fourth panel) CAR cells. Gray denotes the engineered T-
cell. Turquoise represents the extracellular monoclonal antibody variable fragments that
recognize the target antigen, gray represents the hydrophobic transmembrane domain, red
denotes the cytoplasmic CD3-zeta stimulation domain, and turquoise ovals represent the
cytoplasmic co-stimulatory domains such as CD28 and 4-1BB (that help the CAR cells
divide and survive in vivo) (June et al., 2018).
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The foundation of the CAR field was laid in the 1980’s by Israeli immunologist Zelig Eshhar
(reviewed in: Eshhar, 2014), and the technique was further refined by other big-name cancer researchers
such as Steven Rosenberg (National Cancer Institute), Carl June (University of Pennsylvania), and Michel
Sadelain (Memorial Sloan-Kettering Cancer Center). By far, the most successful application of CAR
vaccines to date are those against CD19 for leukemia (reviewed in: Kochenderfer and Rosenberg, 2013;
Jena et al., 2013; June et al., 2018). CARs against CD19 have provided some of the most striking
successes in the entire cancer vaccine field because: 1) CD19 is universally expressed on the surface of all
leukemic B-cells, 2) killing normal B-cells if they happen to express CD19 is not problematic (antibodies
can be provided to the patient passively to compensate for the loss), and 3) CD19 is not expressed outside
the B-cell lineage (so there is little off target killing with the vaccine). Early CAR experiments were
disappointing, and focused on improving CAR design after realizing the injected T-cells quickly die
unless they are co-stimulated in vivo. Table-VII below shows examples of clinical trials using CAR
therapies.
Table-VII: Example Clinical Trial Experiments With CAR Therapies
Target
Antigen Cancer Type Notes Reference
Metastatic
melanoma 15 patients. The CAR cells survived in the peripheral
blood for at least 2 months, and survived for at least
one year in two patients who showed significant tumor
regression.
Morgan et al.,
2006 Rosenberg’s team
α-Folate
Receptor Ovarian cancer Phase-I, 14 patients, but none showed tumor reduction.
PCR analysis showed that the engineered T-cells were
present in the circulation within the first 2 days, but
then quickly declined after one month. Perhaps the T-
cells need a co-stimulator.
Kershaw et al.,
2006 Rosenberg’s team
G-250 Metastatic renal
cell carcinoma 3 patients. Each patient developed liver toxicity so the
treatment had to be discontinued. The patients
continued to show progressive disease. Perhaps the
target antigen is too widespread.
Lamers et al.,
2006
CD20 Lymphoma 3 patients received CARs plus chemoablation to
prevent inhibition of the CARs in vivo. The treatment
was relatively well tolerated. Two patients became
progression-free, with no measurable disease at 12 and
24 months. The third patient initially had a measurable
remission, but relapsed at 12 months.
Till et al., 2008
CD19 Lymphoblastic
leukemia Mouse experiments. Designed a new type of CAR
containing activation domains CD28, CD137
(previously unknown), and/or TCR-zeta. More than
85% of the treated T-cells expressed the engineered
receptor, and the cells survived at least 6 months.
Milone et al.,
2009 Carl June’s team
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CD19 Advanced follicular
lymphoma 1 patient. The first successful clinical treatment of
leukemia using CD19 CARs. Also used a CD28 co-
stimulation receptor. The lymphoma underwent a
dramatic regression, but was this due to the chemo or
the CAR?
Kochenderfer et
al., 2010 Rosenberg’s team
HER-2 (Erbb2)
Colon cancer
metastasized to the
lungs and liver
Tested the vaccine on 1 patient, but he died 5 days after
treatment from a “cytokine storm” (overly elevated
cytokines). The authors speculated that a large number
of perfused CARs localized to the lung cells (with low
but sufficient HER-2) triggering cytokine release. The
study also reminded the researchers that CARs are not
cleared as fast as antibody treatments, so should be
closely monitored.
Morgan et al.,
2010 Rosenberg’s team
CD19 Advanced chronic
lymphocytic
leukemia (CLL)
Breakout year for CARs. CD137 and TCR-zeta co-
stimulators. The CAR cells expanded at least 1000-
fold, migrated to the bone marrow, and continued to
produce functional CARs for at least 6 months, well
beyond the survival of earlier CARs. Each CAR cell
was calculated to destroy about 1,000 cancer cells. One
CLL patient showed complete remission.
Porter et al., 2011 Carl June’s group
CD19 Advanced leukemia 3 CLL patients. Two of the 3 patients showed
complete remission, even 2 years later. Normal B-
cells expressing CD19 were also destroyed causing
grade-3 and 4 B-cell aplasia, but the authors say this
was treatable. These two 2011 studies were later
attributed by Carl June as breaking open the funding
for the entire CAR field.
Kalos et al., 2011 Carl June’s group
CD19 Chronic
lymphocytic
leukemia (CLL)
Also received chemoablation. 8 of the 9 CAR patients
tolerated the treatment well, and 3 of 4 evaluable
patients showed a significant tumor reduction.
Brentjens et al.,
2011 Michel Sadelian’s
team
GD-2 Neuroblastoma Three of 11 patients with active disease achieved
complete remission. Louis et al., 2011
CD19 Relapsed and
refractory acute
lymphoblastic
leukemia (ALL)
2 children with very poor prognosis. The CARs
expanded 1000-fold in vivo, and colonized the bone
marrow and CSF. 1 of the 2 showed complete
remission. The other patient’s tumor lost CD19
expression, so no response. The patients developed
grade-3 and -4 adverse events, including a cytokine
release syndrome, but those events were fully treatable
with cytokine blockade antibodies.
Grupp et al., 2013 Carl June and
Stephan Grupp’s
teams
CD19 Relapsed B-cell
acute
lymphoblastic
leukemia (B-ALL)
5 patients. CD28 and CD3-zeta co-stimulatory
receptors. All 5 patients showed a rapid tumor
eradication, and have no residual disease as assayed
by deep sequencing PCR, although one patient
eventually relapsed. With respect to side-effects, some
patients showed significant cytokine elevations, but
those incidences were treatable with steroid therapy.
Brentjens et al.,
2013 Michel Saedlain’s
team at Sloan
Kettering
70
CD19 Chronic
lymphocytic
leukemia (CLL)
None of the patients received prior chemoablation.
PCR showed CD19-CARs in the blood of 8 of the 10
patients. 3 of the 10 treated patients showed
regressions of their previously untreatable
malignancies. One showed complete remission, while
another showed tumor lysis syndrome as his leukemia
regressed.
Kochenderfer et
al., 2013 Steven
Rosenberg’s team
CD19 Refractory B-ALL 16 patients. 88% of the patients responded well enough
to the therapy to later receive a “routine” allogenic
stem cell transplant. They also identified C-reactive
protein (CRP) as a predictor of which patients will
develop severe cytokine release syndrome (sCRS), and
showed they could be treated with corticosteroids and
IL-6-receptor antibodies.
Davila et al.,
2014 Michel Saedlain’s
team
CD19 Relapsed acute
lymphoblastic
leukemia (ALL)
One of the most spectacular successes in all of
cancer vaccine research. 27 of the 30 patients (90%)
showed complete remission, and 67% were event-free
at 6 months. All 30 developed cytokine-release
syndrome (CRS), but it was effectively treated with
anti-interleukin-6 receptor antibody (tocilizumab), and
the patients remained in remission.
Maude et al.,
2014 Dr. Grupp’s team,
Children’s
Hospital,
Philadelphia
CD19 Refractory B-cell
cancers Phase-I. 21 patients. CD28 and TCR-zeta co-
stimulatory receptors. Pre-treatment chemoablation.
The maximum tolerable dose (MTD) was determined
to be 1 x 106 cells per kg, all the side-effects were
reversible at that dose. The most severe side-effects
were a grade-4 cytokine release syndrome observed in
3 of the 21 patients (14%).
Lee et al., 2015
HER-2 Refractory HER-2
Positive Sarcomas
Phase-I/II trial, escalating doses of HER2-CARs with a
CD28 signaling domain. 19 patients. The cell infusions
were well tolerated with no dose-limiting toxicity. The
CARs persisted for at least 6 weeks in 7 of 9 patients
who received a dose of greater than 1 × 10E6 cells per
m2. Of 17 evaluable patients, 4 had stable disease for 12
weeks to 14 months; 3 of these patients had their tumor
removed, with one showing ≥ 90% necrosis.
Ahmed et al.,
2015
CD19 Refractory Multiple
Myeloma 1 patient vaccinated after myeloablative chemotherapy
(melphalan). CAR therapy lead to a complete response,
with no evidence of cancer progression 12 months post-
treatment.
Garfall et al.,
2015
BCMA
(B-cell
maturation
antigen)
Multiple Myeloma First in-humans clinical trial of CARs against
BCMA. 12 patients, various doses. Observed 1 partial
remission at the 3rd dose level, and at the fourth dose
level (9x10E6 CARs/kg body weight) for two patients,
1 showed undetectable cancer for 17 weeks then
relapse, the other patient showed ongoing partial
remission. The highest dose level-4 caused cytokine
release syndrome in both patients, with fever,
hypotension, dyspnea, and cytopenia.
Ali et al., 2016
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CD22
Pre-B-Cell Acute
Lymphoblastic
Leukemia (B-ALL)
Phase-I trial, in 21 children and adults, including 17
who previously treated with CD19-directed
immunotherapy. Complete remission was observed in
11 of 15 (73%) patients receiving more than 1 x 10E6
CD22-CARs per kg body weight. Median remission
duration was 6 months. Relapses were associated with
decreased CD22 expression.
Fry et al., 2018
CEACAM5
Advanced
CEACAM5+
malignancies
The authors tested a first-generation CAR T-cell
therapy. Patients were treated with Fludarabine pre-
conditioning, followed by CEACAM5-CAR T-cells
(various doses), followed by systemic IL2 support. But
no objective clinical responses were observed. T-cell
engraftment showed a rapid decline within 14 days.
Thistlethwaite et
al., 2017
GD2 Diffuse Midline
Gliomas (DMGs) DMGs are aggressive and universally fatal pediatric
brain cancers. The authors showed that patient-derived
DMGs uniformly express high levels of GD2.
Treatment of these cells with GD2-CARs in vitro
showed strong GD2-dependent cytokine generation and
cell killing. The treatment also cleared tumors from 5
patient-derived xenograft mouse models. The treatment
was generally tolerated in mice, but neuro-
inflammation occurred during the acute phase of anti-
tumor activity resulting in hydrocephalus that was
lethal in some animals. They predict that human DMG
patients, given the neuro-anatomical location of the
midline gliomas, will require careful monitoring and
aggressive care management.
Mount et al.,
2018
GD2
ganglioside
Neuroblastoma
The authors generated variant CARs to improve the
stability and the affinity for the target. One variant
(GD2-E101K) showed enhanced antitumor activity in
GD2+ human neuroblastoma xenograft models, but it
also caused lethal CNS toxicity, including brain CAR
T-cell infiltration and proliferation, and neuronal
destruction. The results highlight the challenges
associated with target antigens also expressed on
normal tissues. While GD2-targeted antibody therapies
have shown some success against neuroblastoma, the
fatal neurotoxicity of GD2-CARs suggests additional
strategies are needed for controlling T-cell function in
the brain.
Richman et al.,
2018
CD19
Advanced Lymphoma
Clinical trial with 22 patients receiving a single dose of
CAR-19 T-cells 2 days after a low-dose chemotherapy.
The overall remission rate was 73% with 55% complete
remissions and 18% partial remissions. Remission
patients had a median peak blood CAR+ cell level of
98/μL compared to 15/μL without remission, and the
high CAR levels associated with high serum IL-15
levels (P = .001) and remissions(P < .001).
Kochenderfer et
al., 2017
72
CD19 Diffuse Large B Cell Lymphoma
KTE-C19 is an autologous CAR T-cell therapy against
CD19 using CD3-zeta and CD28 co-stimulators. It was
was used to treat 7 patients with refractory DLBCL. 1/7
patients 14%) experienced dose-limiting toxicity of
grade-4 cytokine release syndrome (CRS), 1/7 patients
(14%) showed grade >3 CRS, and 4/7 patients (57%)
showed neurotoxicity. All >grade-3 events resolved
within 1 month. 3/7 patients showed clinical responses
(stabilizations) at 12 months. The regimen appears to
be safe for phase 2 studies.
Locke et al., 2017
An assessment of the number of CAR clinical trials as of January of 2018 (June et al., 2018)
identified 253 CAR trials worldwide (Figure-9). The vast majority of CAR trials are being conducted in
China and the U.S. (left panel). Since China ranks 3rd in the world (behind North America and Europe)
for total clinical trials (right panel), their #1 ranking for CAR trials is quite impressive in this area.
Figure-9: Assessment of CAR Clinical Trials Worldwide. The left panel
shows the number of CAR clinical trials assessed as of January of 2018 (total of
253) compared to the total clinical trials in various countries (right panel) (June
et al., 2018).
CAR Problems and Future Directions
Overall, CAR vaccines have shown some of the most spectacular successes in the entire field of
cancer vaccine research. With so many advances and clinical trial successes, it’s hard not to become
excited. As stated in a review on the topic: “although some scientists are urging caution, it is hard not to
be swept up in this moment. No cell therapy has proliferated in the body as well, endured so well, and
slain cancer, quite like this therapy (Couzin-Frankel, 2013). The overall low number of patients treated
so far likely will improve shortly with the exponential increase in the number of clinical trials. The use of
second and third-generation CARs using a variety of activating and co-stimulating domains appears to
have overcome the earlier problem of CAR cell death in vivo. And pre-treating the patients with
chemotherapy to ablate the endogenous B and T-cells appears to have removed the inhibition against
CAR expansion.
73
CRISPR-CAR Combination Therapy One of the most promising and recent innovative uses of CAR cells combines CAR receptor
engineering with the use of CRISPR cas9 to eliminate a host gene. One example showed that using
Lentiviruses and CRISPR greatly increased the efficiency of CAR gene delivery to T-cells. The results
showed CAR expression in human peripheral blood T cells and enhanced effectiveness (Eyquem et al.,
2017), showing better results than typical CAR cells. And in another example, the CRISPR system has
been used to eliminate the gene TRAC which is associated with allo-recognition, and its elimination
might result in CAR cells that could be used universally in any patient (Georgiadis et al., 2018). CD-19
specific CARs were treated with Lentiviruses encoding guide RNAs and Cas9 against TRAC. The
technique produced CAR cells that are far more homogenous than CARs produced using standard
methods (Georgiadis et al., 2018). Furthermore, this combination method produced CAR T-cells with
anti-leukemic effects that are longer lasting than conventionally produced CAR T-cells (Georgiadis et al.,
2018). Ultimately, the combined use of CAR transfections and CRISPR Cas9 transfections is one of the
next steps in CAR T cell therapy.
However, CARs also have problems, including causing patient death in some studies. This is
especially true for CAR treatment of patients with acute leukemia. The following areas are worth
pursuing in the future to make more effective CARs:
1) Side-Effects: The most serious adverse effect observed with CAR trials is patient death (Couzin-
Frankel, 2016; Ledford, 2016). In 2016, 7 trial patients died over about a year due to the CAR therapy
causing fatal brain swelling, and 5 of the 7 patients died in a single clinical trial. Most of the deaths
occurred in adult patients with acute leukemia, and these patients tend to have the worst side-effects due
to rapid expansion of their T-cells (Couzin-Frankel, 2016). The second most serious side-effect is
cytokine release syndrome (CRS), a potentially deadly condition that can cause organ failure (Ledford,
2016). In a large trial of patients with aggressive non-Hodgkin’s lymphoma, about 18% developed CRS
(Ledford, 2016), however this syndrome was often treatable in the patients by blocking the effects of
hormone IL-6 to rapidly reverse the fevers, hypotension, and hypoxia (June et al., 2018).
2) Loss of Target Antigen by the Tumor: The major mode of resistance of some tumors to CAR
therapy is the loss of target antigen by the tumor. This is especially the case for patients with acute
leukemia (June et al., 2018). This underscores the importance of constantly monitoring the patient’s
tumors throughout the entire procedure for target antigen expression, and if a down-regulation occurs,
perhaps the patient could be treated with a CAR targeting a different antigen on the same tumor (if
available). For example, for B-ALL leukemia patients whose tumors no longer expressed CD19, using a
CAR targeting CD22 allowed remissions for at least 6 months (Fry et al., 2018). 3) Failure of the CAR cells to proliferate: The second most common mode of tumor resistance to
CARs is their failure to proliferate in vivo. This is especially the case for patients with chronic cancer
(June et al., 2018). Perhaps these patients would benefit from a combination therapy of CARs plus
checkpoint inhibitor vaccine to activate the immune system. Or alternatively, a CAR using different co-
stimulatory domains would allow CAR proliferation. 4) Correlates of Protection: Some of the studies done with TIL vaccines showed a positive correlation
of a high number of TILs with the best patient prognosis. Is that also true for CARs? Is location
important: Does the location of CARs in the bone marrow affect long-term survival and improve patient
prognosis? Are TILs directed against a patient’s neo-antigens (isolated from the patient’s tumor) better
than CARs directed against a single antigen, such as CD19?
74
5) Combination Therapies: TILs isolated from a patient’s tumor can target multiple target antigens
naturally, while artificially engineered CARs target one antigen. Perhaps it would be worth testing both
CARs and TILs in one patient. Or perhaps a combination of a CAR therapy plus a checkpoint inhibitor
treatment could be tested to help block the shutdown of T-cell activity.
6) Personalized Medicine: Neo-antigens are newly expressed proteins or sugars on the surface of tumor
cells that form following DNA mutations in exons (coding DNA). Because neo-antigens are not
expressed during development, they are viewed as foreign once expressed, and make good target antigens
(Delamarre et al., 2015). The use of new rapid DNA sequencing methods allows a patient’s tumor cells
to be sequenced to analyze for neo-antigen formation (Robbins et al., 2013; Rajasagi et al., 2014;
Schumacher and Schreiber, 2015), but the process needs to be fast, as some patients have a very poor
prognosis (Kalos and June, 2013). For example, patients diagnosed with malignant melanoma in stage-IV
can die within weeks.
Cited CAR References
Ahmed N, Brawley VS, Hegde M, Robertson C, Ghazi A, Gerken C, Liu E, Dakhova O, Ashoori A,
Corder A, Gray T, Wu MF, Liu H, Hicks J, Rainusso N, Dotti G, Mei Z, Grilley B, Gee A, Rooney CM,
Brenner MK, Heslop HE, Wels WS, Wang LL, Anderson P, Gottschalk S (2015) Human Epidermal
Growth Factor Receptor 2 (HER2)-Specific Chimeric Antigen Receptor-Modified T Cells for the
Immunotherapy of HER2-Positive Sarcoma. Journal of Clinical Oncology, 2015 May 20; 33(15): 1688-
1696. doi: 10.1200/JCO.2014.58.0225. Ali SA, Shi V, Maric I, Wang M, Stroncek DF, Rose JJ, Brudno JN, Stetler-Stevenson M, Feldman SA,
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Lit Review Section-5:
Immune Checkpoint Vaccines
Cole Royer
Although some very exciting remissions have been achieved with cancer vaccines, as more
patients have been tested over the years in clinical trials, scientists have come to realize that not all
patients respond to the vaccines. So, recent research has focused on why some tumors are killed and
others are not. One of the most exciting advances in this area is the discovery that T-cells that have
migrated into a patient’s tumor can sometimes become inactivated by immune checkpoint inhibitors
(Hirano et al., 2005; Peggs et al., 2006; Topalian et al., 2012; Sznol and Chen, 2013; Cha et al., 2014;
Herbst et al., 2014). Immune checkpoint inhibitors are receptors, such as PD-1 and CTLA-4, on the
surface of T-cells that bind to inhibitory ligands on other immune cells to inactivate them (reviewed in:
Toplian et al., 2012). Under normal situations, this “checking response” is important for preventing
immune hyper-activation, such as autoimmunity.
In the case of cancer patients, sometimes their tumors present the inhibitory ligands on their
surface, blocking T-cell activation. So, in this case the immune checking response works against the
patient by allowing the tumor to block anti-tumor responses (both native and vaccine) that can kill the
tumor cell. Thus, much vaccine research has focused on using antibodies to block the checkpoint
inhibitors (block the blockers), for example by using antibodies against PD-1 or CTLA-4 to remove the
inhibition against the T-cells that have infiltrated the tumor. This checkpoint inhibitor approach
provides a new and exciting approach for cancer vaccines that is different than other approaches, and is
often used in combination with other therapies. A recent review article on checkpoint vaccines called the
checkpoint therapy approach “arguably one of the most important advances in the history of cancer
treatment” (Ribas and Wolchok, 2018).
PD-1 is inhibitory receptor “Programmed Cell Death-1” located on the surface of activated T-
cells (Freeman et al., 2000; Ribas and Wolchok, 2018). Its ligand is “Programmed Cell Death-Ligand-1
(PD-L1), present on the surface of some tumors and on normal cells exposed to pro-inflammatory
cytokines. When the PD-L1 ligand binds PD-1 receptor, a series of signal transduction events are
activated that decrease T-cell function, such as decreasing T-cell migration and proliferation, restricting
tumor cell killing, and increasing T-cell death (Herbst et al., 2014). Figure-10 below shows how the PD-
1 pathway works to the advantage of tumors. The left panel shows a cancer cell over-expressing PD-L1
protein (blue) on its surface bound to PD-1 receptor (turquoise) on a T-cell. This binding occurs as the T-
cell receptor (dark brown) engages a tumor-specific antigen (yellow) bringing the two cells into close
proximity (McCune, 2018). The right panel shows therapy using antibodies against PD-1 (red) or PD-L1
(yellow) preventing activation of the PD-1 checkpoint pathway, allowing the T-cell to remain active to
kill the tumor cell (McCune, 2018; Abdin et al., 2018).
80
Figure-10: Biology of the PD-1 Receptor. The left panel illustrates T-cell
inactivation when the T-cell is brought into close proximity to a tumor cell, the
ligand PD-L1 (blue) on the surface of the tumor cell engages receptor PD-1
(turquoise). The right panel denotes therapy with antibodies against PD-L1
(yellow) or PD-1 (red) binding their respective receptors to prevent activation of
the PD-1 inhibitory signalling pathway. From National Cancer Institute, 2016.
CTLA-4 is the “Cytotoxic T-Lymphocyte-Associated Protein-4” receptor present on the surface
of T-cells. It was discovered in 1987 (Brunet et al., 1987), and when it is bound to its ligands CD80 or
CD86 lowers T-cell activation (Walunas et al., 1994). Activation of the CTLA-4 pathway is often used
by cancer cells to inactivate tumor-infiltrating lymphocytes (TILs) (reviewed in: Peggs et al., 2006; Cha
et al., 2014). CTLA-4 has been demonstrated to have a potent inhibitory role in regulating T-cell
responses. As opposed to inducing cell death like the PD-1 protein, CTLA-4 inhibits T-cell proliferation
and activation upon binding its ligand (usually protein B7) by outcompeting co-stimulatory molecules
like CD28 that are also trying to bind B7 (Figure-11) (Ribas and Wolchok, 2018). Working with a
similar mechanism as PD-1, under normal conditions during immune activation, B7 on an antigen
presenting cell (yellow) engages co-stimulatory receptor CD28 on a T-cell to help activate it. CTLA-4
(purple) is a break to this activation, moving to the cell surface during activation to outcompete CD28 for
binding B7. Unfortunately, this T-cell inhibition pathway is sometimes used by cancer cells presenting
B7 on their surface, leading to a silencing of the T-cell and evasion of the cancer from the immune
system. Checkpoint therapy drugs for CTLA-4 (i.e. Ipilimumab antibody, red) bind CTLA-4 to block
activation of the inhibitory pathway, preventing the tumor from silencing T-cell signaling. This allows
the T-cells to act at their full capacity and attack the tumor (Sharma and Allison, 2015).
81
Figure-11: Biology of the CTLA-4 Pathway. During immune activation, an
antigen presenting cell (yellow) binds a T-cell (blue) to induce its differentiation
and activation. In addition to the T-cell receptor engaging the presented antigen
(diagram center), a co-stimulatory pathway involving CD28 and B7 interaction
also occurs to further increase the activation. The CTLA-4 pathway is a break
to this activation, being upregulated in the T-cell to outcompete CD28 for B7.
Cancer cells sometimes over-express B7 to engage the CTLA-4 pathway to
inactivate the T-cell, and therapeutic antibodies against CTLA-4 (red) prevent
this inactivation. From Lee et al., 2012.
The incredible success of checkpoint vaccines is illustrated by the exponential increase in the
number of human clinical trials using these inhibitors (Figure-12). From 2009 to 2017, the number of
clinical trials using checkpoint inhibitors increased from 1 trial (with 136 patients) to 469 trials (with
52,539 patients). The checkpoint treatments are often used in combination with other therapies (lower
row in the diagram), the most frequent being other immune therapies.
Figure-12: Exponential Increase of Clinical Trials
Using Checkpoint Inhibitors. The graph shows the
exponential increase in the patients enrolled in clinical
trials from 2009 to 2017 using checkpoint inhibitors
(upper graph), and the number of clinical trials (middle
row). The lower row denotes the combination drug used
with the checkpoint drug, with the largest cohort being
another immune drug (lower left). Figure is from
Kaiser, 2018.
82
Checkpoint Vaccine Examples
Figure-13 below shows the time-line of FDA approval for 6 checkpoint antibodies and one
combination therapy. The green dots show the date of first patient treatment with the drug, and the red
dots indicate the date of FDA approval for using that particular antibody to treat a specific form of cancer.
The first checkpoint antibody used in a patient was Ipilimumab, an antibody against CTLA-4. It was
first used in a patient in June of 2000, and in 2011 was FDA-approved for melanoma patients. The second
checkpoint antibody used was Nivolumab (marketed as Opdivo), an antibody against PD-1. It was first
used on a patient in 2006, and from 2014 to the present has been FDA-approved for treating melanoma
(Topalian et al., 2014), non-small cell lung carcinoma, renal cell carcinoma, Hodgkin’s lymphoma
(Ansell et al., 2015), head and neck cancer, urothelial cancer, high microsatellite instability, and
hepatocellular carcinoma (Gettinger et al., 2015; Rizvi et al., 2015; Tanner, 2015).
Figure-13: Time-Line of FDA Approval for Several Checkpoint
Vaccines. The green dots denote the date of first patient treatment with the
drug, and the red dots indicate the date of FDA approval for using that particular
antibody to treat a specific form of cancer. Figure is from Ribas and Wolchok,
2018.
A recent trend with checkpoint vaccines is their combination with antibodies directed against
tumors, and these studies have produced some spectacular successes. Table-VIII below shows example
studies with checkpoint vaccines.
Table-VIII: Example Studies Using Checkpoint Vaccines
Target Notes Side-Effects Reference
Phase-I study of 39 patients with advanced
metastatic melanoma, colorectal cancer
(CRC), castrate-resistant prostate cancer,
non-small-cell lung cancer (NSCLC), or
renal cell carcinoma (RCC). Anti-PD-1
(MDX-1106) treatment. The results showed
one durable complete response, and two
partial responses. The serum half-life of anti-
PD-1 was 12 to 20 days.
The anti-PD-1 was well
tolerated, with one serious
adverse event of
inflammatory colitis.
Brahmer et al.,
2010
83
PD-1
Phase-I multi-center Phase-I trial of anti-PD-
L1 therapy, 207 patients with non-small-cell
lung cancer, melanoma, colorectal cancer,
renal-cell cancer, ovarian cancer, pancreatic
cancer, gastric cancer, and breast cancer.
Among patients with a response that could
be evaluated, an objective response (a
complete or partial response) was observed
in 9 of 52 patients with melanoma, 2 of 17
with renal-cell cancer, 5 of 49 with non-
small-cell lung cancer, and 1 of 17 with
ovarian cancer.
Grade-3 or 4 toxic effects
related to treatment occurred
in 9% of patients.
Bramer et al.,
2012
International Phase-II study, anti-PD-1
monoclonal antibody, in 36 patients with
diffuse large B-cell lymphoma
(DLBCL). Among the 35 patients with
measurable disease after stem cell transplant,
the overall response rate after antibody
treatment was 51%.
Toxicity was mild.
Armand et al.,
2013
135 patients with advanced melanoma, anti-
PD-1 antibody treatment in patients
previously receiving CTLA-4 antibody and
those who had not. The confirmed response
rate across all dose cohorts was 38% The
response rate did not differ significantly
between patients who had received prior
anti-CTLA-4 treatment and those who had
not.
Common adverse events
attributed to treatment were
grade-1 or 2, including
fatigue, rash, pruritus, and
diarrhea.
Hamid et al.,
2013
International, multi-center Phase-I trial of
173 patients with advanced melanoma
previously treated with anti-CTLA-4
antibody. The overall response rate was
26%.
The treatment was well
tolerated. There were no
drug-related deaths. The most
common drug-related adverse
events in the 10 mg/kg group
were fatigue (37%), pruritus
(19%), and rash (18%).
Grade-3 fatigue was reported
in five (3%) patients.
Robert et al.,
2014
The treated 107 melanoma patients showed a
mean overall survival of 16.8 months, with
1- year and 2-year survival rates of 62% and
43%, respectively.
The antibody safety was
“acceptable”, with toxicity
rates similar to previous
reports.
Topalian et al.,
2014
Phase-III controlled study, Nivolumab anti-
PD-1 therapy versus dacarbazine
chemotherapy, 418 patients with metastatic
melanoma. At 1 year, the overall rate of
survival was 72.9% in the antibody group
compared to 42.1% in the chemotherapy
group.
Common adverse events
associated with the antibody
treatment included fatigue,
pruritus, and nausea, with
grade-3 or 4 events in 11.7%
of the patients treated with
antibody and 17.6% treated
with chemotherapy.
Robert et al.,
2015
84
23 patients with relapsed or refractory
Hodgkin's lymphoma received Nivolumab
anti-PD-1 treatment. A high percent of the
patients had received previous treatments
with stem-cell transplantation or
Brentuximab vedotin (antibody-drug
conjugate targeting CD30). An objective
response was reported in 87% of the
patients, including 17% with a complete
response and 70% with a partial response.
Drug-related adverse events
of any grade occurred in 78%
of the patients, grade-3 events
in 22%. and of grade 3
occurred in 78% and 22% of
patients, respectively.
Discontinuation of the study
due to the drug occurred in 2
patients.
Ansell et al.,
2015
Phase-II study of 22 patients with non-small
cell lung cancer (NSCLC). the drug
produced “durable immune responses and
encouraging survival rates
14% of the patients showed
grade-3 or -4 treatment-
related adverse events.
Gettinger et al.,
2015
Non-small cell lung cancer patients.
Analyzed non-synonymous mutations to
show that higher neo-antigen formation
(more targets) correlated with better clinical
benefits and progression-free patient
survivals.
Rizvi et al.,
2015
600 patients with non-small cell lung cancer.
The median survival rate increased from 9
months (chemotherapy alone) to 12 months
(for the immunotherapy group), and the
tumors shrank in 12% of the chemotherapy
patients versus 20% of the immunotherapy
patients.
Tanner, 2015
Phase-I trial for 655 patients with advanced
metastatic melanoma using humanized anti-
PD-1 monoclonal antibody Pembrolizumab,
performed in academic medical centers in
Australia, Canada, France, and the United
States. An objective response was reported
in 194 of 581 patients (33%). 44% (90/205)
had response duration of at least 1 year.
Ribas et al.,
2016
Multicenter Phase-II trial of 315 patients
with metastatic urothelial carcinoma that
have failed standard platinum chemotherapy
using humanized antibody against PD-
L1. The antibody-treated group showed an
overall response rate of 15%, compared to a
historical response rate of 10%.
Grade 3-4 treatment-related
adverse events occurred in 50
(16%) of 310 treated patients.
Fatigue was the most
common (5 patients, 2%). No
treatment-related deaths
occurred during the study.
Rosenberg et
al., 2016
112 melanoma patients treated with anti-PD-
1 therapy. Identified oral and gut
microbiome differences in patient responders
versus non-responders. Responder gut
microbiomes showed greater microbial
diversity, higher abundance of
Ruminococcaceae, and enrichment of
anabolic pathways. Mice receiving patient
Gopalakrishnan
et al., 2018
85
responder fecal transplants showed better
vaccine responses.
Determined that a primary mode of epithelial
cancer patient resistance to anti-PD-1
therapy is the gut microbiome
composition. Antibiotics tended to lower the
clinical benefit the therapy, while fecal
microbiota transplantation (FMT) from
responder patients into mice improved the
treatment. Responders tended to have high
levels of Akkermansia muciniphila, and
supplementation with this microbe tended to
improve outcomes in mouse models.
Routy et al.,
2018
The team developed mouse models of
colorectal cancer with increased levels of
TGFβ in the tumor microenvironment to
mimic patients with T-cell exclusion and
resistance to anti-PD-1 therapy. The mice
showed limited response to anti-PD-1
therapy. Blocking the TGFβ signaling
pathway unleashed a potent and enduring
cytoxoxic T-cell response against the tumors
and improved the anti-PD-1 response. Thus,
TGFβ in the tumor microenvironment is a
primary mechanism of tumor immune
evasion.
Tauriello et al.,
2018
Performed a risk analysis for anti-PD-1
Nivolumab for hepatotoxicity. Analyzed all
Phase-I through Phase-III trials through
December 2016 for elevated levels of liver
enzymes in the blood: aspartate
aminotransferase (AST) and alanine
aminotransferase (ALT). Overall
hepatotoxicity was only 5.4%, and high-
grade toxicity was 1.6%.
Zarrabi and Wu,
2018
CTLA-4
9 patients with various cancers. CTLA-4
antibody treatment caused extensive tumor
necrosis in three of three (100%) metastatic
melanoma patients, and the reduction or
stabilization of cancer in two of two (100%)
metastatic ovarian carcinoma patients, but
caused no reduction in 4 of 4 metastatic
melanoma patients previously immunized
with defined melanoma antigens.
No serious toxicities directly
attributable to the antibody
therapy were observed.
Hodi et al.,
2003
Phase-I trial. 39 patients with solid
malignancies (34 melanoma, 4 renal cell,
and 1 colon, n = 1). The maximum tolerated
dose (MTD) was determined to be 15
mg/kg. 2 patients experienced complete
responses, and two experienced partial
responses.
Dose-limiting toxicities and
autoimmune phenomena
included diarrhea, dermatitis,
vitiligo, pan hypo-pituitarism
and hyper-thyroidism.
Ribas et al.,
2005
86
CTLA-4
Metastatic melanoma patients. The median
overall survival of patients receiving the
CTLA-4 antibody + gp100 peptide vaccine
was 10 months compared to 6.4 months for
those receiving only the gp100.
The side effects were severe
in only 10-15% of the
patients receiving both
treatments, and in only 3% of
the patients receiving
gp100. Most were
manageable. 2.1% of the
patients died from the study,
7 related to immune adverse
events.
Hodi et al.,
2010
The article discusses the
different kinds of immune-
related adverse events
associated with CTLA-4
treatment, and the necessary
treatments to manage them.
They conclude that one of the
most important aspects of
side-effect treatment is early
recognition.
Weber et al.,
2012
11 melanoma patients. Performed whole
exome sequencing was performed to
correlate which neo-antigens correlate with
best improvements using CTLA-4 antibody
treatments.
Snyder et al.,
2014
Tested advanced melanoma patients with
CTLA-4 antibody if they did not respond to
PD-1 antibody. 31.7% showed positive
responses compared to 10.6% with
chemotherapy.
Noted grade-3 to 4 (serious)
adverse events in 5% of
antibody-treated patients
versus 9% for chemotherapy.
There were no treatment-
related deaths.
Weber et al.,
2015
Metastatic osteosarcoma. The tumor burden
decreased, and the survival rate increased.
Lussier et al.,
2015
A pooled analysis of overall survival data
from 1,861 patients from 10 prospective and
two retrospective studies of ipilimumab,
including 2 phase-III trials. Patients were
previously treated (n = 1,257) or treatment
naive (n = 604), and the majority of patients
received ipilimumab 3 mg/kg (n = 965) or 10
mg/kg (n = 706). Of the 1,861 patients, the
median overall survival was 11.4 months,
including 254 with at least 3 years of
survival.
Schadendorf et
al., 2015
A review of the data of 4 Phase-I and II trials
at 2 sites for 143 patients with advanced
melanoma. The median overall survival was
13 months, with a 5 year survival rate of
20%, and a 12.5 year survival rate 16%.
Eroglu et al.,
2015
87
Analyzed 536 metastatic cancer patients
treated with anti-PD-1, PD-L1, or CTLA-4
immunotherapies for liver related side-
effects. Only 19 patients (3.5%) needed
referral to the liver unit for grade ≥3
hepatitis. No patients developed hepatic
failure. 6 patients improved spontaneously;
the remainder received various doses of oral
corticosteroids. Liver biopsy was helpful for
the diagnosis and evaluation of the severity
of liver injury. The severity of liver injury
was helpful for tailoring patient
management, which does not require
systemic corticosteroid administration.
De Martin et al.,
2018
Combination
Treatments
PD-1 + CTLA-4. Melanoma patients. 53%
of the combination patients showed a tumor
reduction of 80% or more, compared to only
20% for single antibody treatments.
Grade-3 and 4 side-effects
occurred in 53% of the
combination patients
compared to 18% in the
single antibody patients. The
side-effects were generally
reversible.
Wolchok et al.
2013
PD-1 + CTLA-4. Various cancers. Inverse
treatments, used the opposite antibody
against patients showing resistance to the
first antibody.
Found that in most cases, the
second antibody was well
received.
Weber et al.,
2013
PD-1 + CTLA-4. Studied metastatic
osteosarcoma in mice. The combination
treatment prevented tumor escape and
allowed complete control of the cancer.
Lussier et al.,
2015
Phase-III trial of 1096 patients with
advanced clear-cell renal-cell carcinoma
with antibodies to PD-1 + CTLA-4. At 25.2
months, the 18-month survival rate was 75%
for the combination versus 60% for
treatment with a tyrosine kinase inhibitor.
Treatment-related adverse
events occurred in 509 of 547
patients (93%) in the
combination group versus
521 of 535 patients (97%) in
the kinase inhibitor group.
Treatment-related adverse
events causing termination
from the trial occurred in
22% and 12% of the patients,
respectively.
Motzer et al.,
2018
Cancer cells sometimes express TGF-β
which activates regulatory T-cells to inhibit
CD8+ cytotoxic T-cells. The authors
developed a bi-specific antibody, with one
arm recognizing CTLA-4 or PD-1, and the
other arm representing the ectodomain of the
TGFβ receptor II (to bind and sequester
TGFβ). The bi-specific therapy was more
effective at inducing tumor regression (and
reducing regulatory T-cells) than the mono-
specific antibody.
Ravi et al., 2018
88
Checkpoint Vaccine Problems and Future Directions
Some of the data using checkpoint inhibitor vaccines is striking, including some complete
remissions from very difficult cancers. The data also shows that using a combination of antibodies (for
example against PD-1 and CTLA-4, or combining PD-1 with a bi-specific antibody) may produce better
data than using either antibody alone. But as groundbreaking and promising as immune checkpoint
vaccines have been, several factors are drawbacks to their use. Blocking the immune blockers can
sometimes activate the immune system too far, producing autoimmunity or inflammation (Melero et al.,
2007; Frankel, 2017), so inflammation should be constantly monitored during the treatments. Other
studies showed the treatments caused grade-3 and -4 (serious) side-effects, some even resulting in death
(Eggermont et al., 2016). Although most of the side-effects appeared to be transient and treatable. The
side-effects were especially treatable if they were detected early, so these events should be constantly
monitored throughout the entire treatment. In other cases, the patient simply did not respond to the
treatment. Even in studies with the best objective response rates, roughly 30% of patients would see no
response. Finally, as with many aspects of our healthcare system, the cost of these drugs can put them out
of reach for many patients, with one course costing up to $150,000 (McCune, 2018). These problems
should be addressed with future experiments.
High Incidence of Complications/Side-Effects
In nearly all the clinical trials examined in this section of the Literature Review, regardless of
drug, dosage, or disease, a large percentage of patients suffered severe (grade 3 or 4) side-effects caused
by the treatment. One study saw nearly half of the patients with side-effects, with 1 in 5 patients being
grade-3 or 4, while another study saw 68% with adverse effects, with 1 patient in 10 being serious
(Topalian et al., 2012; Weber et al., 2015). Another study noted that while most of the side-effects were
manageable, 2.1% of the patients died from the study, 7 related to immune adverse events (Hodi et al.,
2010).
When combining the individual drugs Ipilimumab and Nivolumab into one therapy, the rate of
grade-3 and 4 adverse effects was 53% compared to 18% in the single antibody patients (Wolchok et al.,
2013). Another combination trial observed adverse events in 93% of 547 patients, with those events
causing termination from the trial in 22% of the patients (Motzer et al., 2018). While these adverse
incidences are troubling, they are not out of the norm for cancer therapies. Indeed, some of the trials
reported less frequent occurrence of severe adverse effects than standard chemotherapy (Abdin et al.,
2018). And in most cases, the side-effects were transient and treatable, with a prognosis far better than
the terminal cancer being treated. However, any treatment where a large portion of patients have high
grade complications is not ideal, and this keeps the checkpoint vaccines from being a first-line treatment.
Autoimmune Disorders
Most of the adverse side-effects described above were autoimmune related. The most commonly
observed were thyroid disease, type-1 diabetes, colitis, and liver damage. Checkpoint inhibitors dial up
the immune system beyond physiologically normal levels to overcome the mechanisms that tumors
deploy to hide from the immune cells, so it is natural to see how autoimmune disorders could rise from
this strengthened immune system. The checkpoint inhibitor antibodies can act on normal cells as well the
cancer, allowing the immune system to overcome an important block for the body (Frankel, 2017). Liver
damage (hepatitis) was a particularly well reported side effect, with one study seeing 3.5% of all
checkpoint patients with hepatitis severe enough to require hospitalization (De Martin et al.,
2018). Another study with a 20% rate of grade-3 or 4 complications showed 10.3% with liver toxicity
(Zarrabi and Wu, 2018). One of the more serious autoimmune diseases seen was autoimmune
myocarditis, an immune attack on the heart which can be fatal (Frankel, 2017). Fortunately, this was rare
and most of these autoimmune side-effects were treatable and preferable to progression of
89
cancer. However, their burden and potential fatality must be taken into consideration before checkpoint-
based treatment can be initiated (Zarrabi and Wu, 2018).
Low Response Rate
The clinical trials examined here show that even in the best scenarios, up to one in three patients
had no response to the checkpoint therapy. And some types of cancer simply do not appear to respond to
checkpoint inhibitors (Ravi et al., 2018). New research is focusing on how the specific genetic makeup
and personal microenvironment of the patient’s tumor and gut can determine how effective the checkpoint
therapy might be, hopefully identifying a variety of molecular and microbial biomarkers that can be used
to personalize therapy and determine which patients will best respond.
A recent fascinating finding relates to the hormone transforming growth factor-beta (TGF-β) and
its potential role in determining the receptibility of a tumor to a checkpoint therapy. TGF-β is a multi-
functional cytokine with a critical role in regulating the adaptive immune system. When secreted into the
bloodstream during an immune response, TGF-β restricts the differentiation of helper T-cells, stops the
development of memory T-cells, and induces the production of regulatory T-cells during an immune
response. Like PD-1 and CTLA-4, TGF-β protects healthy somatic cells from an overactive immune
system and prevents an autoimmune response. However, many tumors also over-express TGF-β to evade
the immune system. In tumors that do this, checkpoint therapy targeting PD-1 has not been effective;
although the PD-1/PD-L1 system was inactivated by the therapy, the related cytokine response was still
keeping the immune system in check in the tumor microenvironment. The best results for these tumors
came when an antibody targeting TGF-β was used in conjunction with a checkpoint inhibitor to block
both mechanisms of immune system evasion (Ravi et al., 2018). Another study supporting these results
showed that a tumor microenvironment with high levels of TGF-β had almost no response to checkpoint
therapy, but showed a potent response after inhibition of TGF-β (Tauriello et al., 2018). These results
point to the potential use of TGF-β levels as a biomarker for identifying which specific patients have a
cancer microenvironment that would respond to checkpoint therapy alone and those that would require a
combination treatment.
Other recent work has shown that the bacterial composition of the patient’s gut microbiome can
modulate the effectiveness of checkpoint inhibitors. Bacterial mediated interactions with the immune
system are essential for its normal function, and by extension optimal checkpoint inhibitor therapy
outcomes (Jobin, 2018). The gut provides an environment that houses many immune cells. Beneficial gut
bacteria can cause these immune cells to secrete antibodies. Patients who responded to checkpoint
therapy were shown to have functional differences in the types of bacteria that predominated their gut
relative to patients that did not respond (Gopalakrishnan et al., 2018). One study found that patients who
responded to Nivolumab had an abundance of bacteria of the genus Faecalibacterium, while non-
responders had a much lower abundance of this microbe. This team also showed that targeted microbial
enrichment of non-responding patients with the Faecalibacterium correlated with a greater response to
PD-1 therapy and an increase of T-cells in the tumor (Jobin, 2018). Another study showed that resistance
to checkpoint therapy can be attributed to an abnormal gut microbiome. When antibiotics were
prescribed to return the gut microbiome to its optimal state, the effectiveness of checkpoint inhibitors
increased (Routy et al., 2018). The same study correlated the abundance of the species Akkermansia
muciniphila to checkpoint efficacy, as oral supplementation of this microbe increased therapy results
(Routy et al., 2018). These studies point to the composition of a patient’s gut fauna as a promising
indicator of whether they will respond to checkpoint therapy, and also provide hope that those who do not
have an optimal gut microbiome can be given supplemental treatment that will increase their chances of a
positive response.
A third variable that has received increased attention for its role in improving checkpoint therapy
effectiveness is the human leukocyte antigen (HLA) class of molecules. The HLAs are a set of cellular
surface proteins that immune cells use to distinguish the body’s cells from foreign cells. Every person has
90
a slightly different set of HLAs that their immune system uses as markers, and the exact makeup of these
proteins is determined by the genotype of the HLA gene complex (American Cancer Society, 2017). One
study demonstrated that melanoma patients with increased heterozygosity in their HLA genes had
increased survival rates compared to patients with a high level of HLA homozygosity (Chowell et al.,
2018). A meta-analysis of the outcomes of over 1,500 cancer patients treated with checkpoint therapy
supported these conclusions, finding that better outcomes often occurred in patients with HLA subtype
heterozygosity. These results make sense because checkpoint therapy depends on the ability of the
immune system to recognize a tumor as an invading cell, and this is easier if the somatic cells have a
more complex and varied identification system (from heterozygosity of the HLA genes). It is easier for a
tumor to avoid detection when HLA is homozygous because the identification proteins on somatic cells
will be less complex and easier to mimic. The same study also showed that a specific subtype of HLA
(HLA-B44) gave the best outcomes for the checkpoint patients, and the HLA-B62 subtype gave a poor
outcome. It is not well understood why the subtypes affected checkpoint therapy this way, but this work
showed that a patient’s HLA genetic makeup might be used as a biomarker to predict effectiveness of the
checkpoint therapy (Chowell et al., 2018).
As this last section has shown, numerous factors beyond the type and stage of the cancer affect
the success of checkpoint therapy. Individual differences in the tumor microenvironment (TGF-β levels),
the gut microbiome, and patient HLA immunogenetics can explain why two people with the same disease
respond so differently to therapy. These individualized determinants have led to the rise of personalized
therapy using these individual differences as biomarkers to indicate whether a patient will respond well to
the checkpoint inhibitor therapy. However, the use of biomarkers is not perfect. Ledford 2018 showed
that biomarker tests can be inconclusive or give false negatives. Nevertheless, individual differences in
patients and their tumors have been clearly demonstrated to determine the effectiveness of
immunotherapy, even though such experiments remain in their infancy. More work to solidify the
identification of biomarkers and the patients best fit for checkpoint therapy is needed for providing more
positive data for the FDA approval of more immune treatments (Leford, 2018).
Recent Failed Clinical Trial
The checkpoint vaccine field also recently suffered a setback with the failure of one of its Phase-
III clinical trials (Garber, 2018). The Phase-III trial was being conducted by the biotech company Incyte
using a combination treatment of Opdivo (PD-1 antibody) and Epacadostat. Epacadostat blocks the
enzyme indoleamine 2,3-dioxygenbase (IDO) which is thought to become activated in T-cells that have
been treated with a checkpoint inhibitor creating a “negative feedback loop” to put a brake on the
activated T-cells. But this feedback loop works against the cancer treatment, so scientists thought that
inhibiting IDO might allow a more prolonged activation of the T-cells. In earlier Phase-I and Phase-II
trials, the combination treatment worked well, but in the recent Phase-III trial the combination was no
better than Opdivo alone. So, maybe the IDO enzyme doesn’t really block the activated T-cells as
scientists believed? Or maybe the wrong patients were treated? Unfortunately, the Incyte failure caused
three other companies to cancel, suspend, or downsize their Phase-III trials with Epacadostat (Garber,
2018).
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METHODS
To accomplish project objective-1, we performed an extensive review of the available research
literature, including reputable academic journal articles, relevant books, scholarly websites, newspaper
articles, and other pertinent materials.
To accomplish objective-2, we conducted a set of interviews with various biomedical
researchers who have performed cancer vaccine research on either animals or humans. We also
interviewed scientists who have used traditional cancer fighting technologies, to determine their range of
opinions on newer forms of treatment.
Who: The “stakeholders” (interviewees) included academic biomedical experts on cancer
vaccines and traditional cancer therapies, and general health experts on cancer. These experts helped
answer questions resulting from our Lit Review search, and helped us prioritize any remaining problems.
Some of the stakeholders interviewed were initially identified by referral from the project advisor, Prof.
David Adams. Other interviewees were identified from the published literature as authors on key
scientific papers, or were referred to us from the initial interviewees.
Where and When: Once contact was made with a potential interviewee (see below), a time and
place was set up for the interview to be performed at the interviewee’s workplace. Whenever possible,
interviews were conducted in person, although most were conducted by email, phone, or Skype.
How: Our first round of prospective interviewees was contacted by email and/or phone. If no
response was received, we used follow-up emails and phone calls. We developed our interview questions
(see preliminary questions in the Appendix) based on our review of the literature, and tailored the
questions to the interviewee’s expertise. Based on the interviewee’s response to our first questions, in
some cases we asked follow-up questions to clarify the information provided, or to press the interviewee
for more information. The preliminary list of questions in the Appendix covers the full range of topics
needed to cover our project.
With respect to the method of the interview, whenever possible each interview involved two team
members, so that one member could ask questions while the other member wrote detailed notes, and vice
versa. We asked whether the interviewee consented to be digitally recorded, and if not, we used written
notes or emails as the main method of recording the conversation.
At the start of the interview, we informed the interviewee about the purpose of our project, and
asked for permission to quote them (see draft interview preamble in the Appendix). We explained how we
will protect their confidentiality, if necessary, by giving them the right to review any quotations used in
the final published report, explaining that the interview is voluntary, and explaining that they may stop the
interview at any time or refuse to answer any question.
After the interview, we asked each interviewee for permission to follow-up with them at a later
date if needed to fill in any gaps in the information. And, as mentioned above, we asked the interviewee
to recommend other potential stakeholders we might interview, to further increase the number of
interviews with key individuals.
With respect to the total number of interviews needed for our project, we stopped interviewing
additional subjects when we obtained a sufficient amount of information to represent all sides of the
cancer vaccine story, good and bad, and when all unclear points had been clarified.
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To accomplish objectives-3 and 4, the group synthesized all of the information collected in the
literature research, interviews, and follow-up interviews, to ascertain the strength of the evidence, and to
create recommendations for further research.
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RESULTS / FINDINGS
Our review of the cancer vaccine literature identified several problems that needed further
clarification in interviews. We performed interviews with a variety of scientists, including those who
helped develop cancer vaccines, doctors who performed cancer vaccine clinical trials, and scientists
actively engaged in developing new generations of cancer vaccine drugs. We chose to focus on two main
problems and directions: 1) What causes vaccine side-effects, and what new approaches might minimize
them? 2) Why are some patients resistant to vaccines, and what new approaches might improve this?
Results for Therapeutic Antibody Vaccines A major problem with cancer vaccines is that a substantial proportion of the patient’s tumors do
not respond to them. To understand this problem further, we interviewed Dr. Sergey E. Sedykh of the
Laboratory of Repair Enzymes, Siberian Branch of the Russian Academy of Sciences Institute of
Chemical Biology and Fundamental Medicine, Novosibirsk State University, Novosibirsk, Russia. Dr.
Sedykh was corresponding author on a 2018 review article on bi-specific antibodies: Sedykh et al., 2018,
Bispecific antibodies: design, therapy, perspectives. Drug Design, Development, and Therapy, 2018 Jan
22; 12: 195-208. When asked his opinion on the leading cause of resistance to bi-specific antibody
therapies, he replied: “My opinion is that bispecific antibodies (like blinatumomab and catumaxomab) act
by attracting a T-cell (via the CD3 receptor) to a tumor cell, but if there are few T-cells remaining in the
patient [for example due to a prior chemotherapy], the patient cannot fight the cancer. The down-
regulation of surface antigens on cancer cells may be another tumor-evolution route of cancer cell
resistance. In some cases, therapeutic BsAbs are considered as the auxiliary treatment after inductional
and consolidation therapy”. So, Dr. Sedykh indicated that tumor resistance to bi-specific antibody
therapy can result from a general low number of T-cells to attract to the tumor (with the anti-CD3
portion), and from the down-regulation of target antigen expression.
Our Lit Review indicated that one approach for overcoming resistance is to change the
type of vaccine used. A very good example of this is the paper: Rothe et al., 2015, A phase-I study
of the bispecific anti-CD30/CD16A antibody construct AFM13 in patients with relapsed or refractory
Hodgkin lymphoma. Blood, 2015 Jun 25; 125(26): 4024-4031. The authors used bispecific antibody
AFM13, which has affinities for CD30 (present in lymphomas) and CD16A (which recruits natural killer
cells to the tumor instead of T-cells). This was a Phase-I dose-escalation study (doses of 0.01 to 7 mg/kg
body weight) of 28 patients with heavily pretreated relapsed or refractory Hodgkin lymphoma. Three of
26 evaluable patients (11.5%) achieved partial remission, and 13 patients (50%) achieved stable disease.
Importantly, AFM13 was active in brentuximab vedotin (CD30)-refractory patients. A phase 2 study is
currently planned. Adverse events were generally mild to moderate. So, attracting NK cells to a tumor
might be an alternative approach for treating patients resistant to T-cell attracting therapies. To shed
more light on this topic, we interviewed the corresponding author of the article: Dr. Andreas
Engert, Professor of Internal Medicine, Hematology & Oncology, and Chairman of the German Hodgkin
Study Group, Department of Internal Medicine, University Hospital of Cologne, Germany. When asked
whether their NK-recruiting strategy to switch the method of cell killing might work for other types of
cancers besides Kodgkin lymphoma, he stated: “We have only used this approach in Hodgkin lymphoma,
but it might certainly be possible that this also works in other malignancies, we have not pursued this
yet”. Thus, Dr. Engert indicated that this new approach of switching the method of cell killing might
indeed work with other types of cancers, but they have not yet tested it. Another possible mechanism for tumor resistance is a mutation occurs that switches the tumor
from one growth signaling pathway to another. An example of this is the article: Lieu et al., 2017, A
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Phase Ib Dose-Escalation Study of the Safety, Tolerability, and Pharmacokinetics of Cobimetinib and
Duligotuzumab in Patients with Previously Treated Locally Advanced or Metastatic Cancers with Mutant
KRAS. Oncologist, 2017 Sep; 22(9): 1024-e89. The authors investigated patients with KRAS-mutant
tumors that possess abnormal MAPK pathway signaling and cell proliferation. They did a Phase-IB dose-
escalation study of a combination of Cobimetinib (which blocks MAPK signaling) and the bi-specific
antibody duligotuzumab (which inhibits ligand binding to two types of receptors: EGFR and human
epidermal growth factor receptor 3 (HER3). They enrolled 23 patients KRAS-mutant tumors. Nine of
the 23 patients (39%) showed stable disease, but 14 were non-responders. To get at the basis of the tumor
resistance, we interviewed the corresponding author on the article: Dr. Christopher H. Lieu, MD,
Director of GI Medical Oncology, and Deputy Associate Director for Clinical Research, University of
Colorado Anschutz Medical Campus, Division of Medical Oncology, Aurora, Colorado. When asked his
opinion about why the patients were non-reponders, he replied: “I think if a patient’s tumor is not
addicted to the MAPK pathway, they may be using another growth pathway to grow and metastasize. In
our case, the non-responders may not have needed the MAPK pathway (which both of our drugs inhibit),
but may have used another growth pathway that we were not blocking”. Thus, according to Dr. Lieu,
when using therapies that work by binding to receptors to block a specific cell growth pathway, to
determine whether a particular tumor will respond to the antibody, the tumor needs to be verified as being
dependent on that specific pathway, otherwise the treatment won’t work.
Reduction of target antigen expression in a portion of the tumor is another mechanism of
resistance. This situation was seen in a recent 2018 paper: Bosco et al., 2018, Preclinical evaluation of a
GFRA1-targeted antibody-drug conjugate in breast cancer. Oncotarget, 2018 May 1; 9(33): 22960-22975.
The authors used a genomics approach to identify membrane-localized tumor-associated antigens (TAAs)
in breast cancer cells that might serve as a target for antibody-drug conjugate (ADC) therapy. They
identified glial cell line-derived neurotrophic factor (GDNF) family receptor-α1 (GFRA1) as a breast
cancer tumor-associated antigen. They determined that GFRA1 shows limited expression in normal cells,
over-expression in some breast tumor subtypes, and rapid internalization, making it a good ADC target.
Their GFRA-targeting ADC showed strong anti-tumor activity against GFRA1-positive tumor cell lines
in vitro, and in vivo against patient-derived human cancers in mouse xenograft models. The safety profile
showed only transient problems in the bone marrow and peripheral blood, consistent with well known
off-target effects of their chosen cytotoxic cargo. To determine the proportion of breast cancer patients
that might benefit from anti-GFRA therapy, we interviewed the corresponding author of the paper: Dr.
Emily E. Bosco, PhD, Scientist-II, Oncology Research, MedImmune, Gaithersburg, Maryland. When
asked her opinion of what percent of breast cancer patients might express GFRA and benefit from their
ADC, she replied: “we would first treat the moderate and strong GFRA-expressing breast cancer patients,
and based on immunohistochemistry (IHC) these patients represent about 20% of estrogen receptor-
positive breast cancer patients, and about 9% of triple negative breast cancer patients”. So, Dr. Bosco
indicates that based on their own immunohistochemical staining of breast cancer tumors, about 29% of
breast cancer patients might benefit from the GFRA-targeting ADC drug. Presumably, the other breast
cancer patients would need to be treated with a drug targeting a different surface antigen, such as HER2
or HER3.
A problem frequently encountered with new therapies is a lack of negative controls in the clinical
trials. In the case of cancer vaccines, the patients are not allowed to receive the new therapy unless the
cancer relapses from the patient’s previous treatments. And the prognosis is very poor for relapsed
patients, so almost any increase in patient survival is significant for these populations. An example of this
problem is the article: Trněný et al., 2018, A Phase 2 multicenter study of the anti-CD19 antibody drug
conjugate coltuximab ravtansine (SAR3419) in patients with relapsed or refractory diffuse large B-cell
lymphoma previously treated with rituximab-based immunotherapy. Haematologica, 2018 May 10. The
authors performed a Phase-II multi-center clinical trial on the safety and efficacy of their anti-CD19-
targeting antibody-drug conjugate (ADC) Coltuximab ravtansine. They analyzed patients with relapsed
or refractory diffuse large B-cell lymphoma who had previously received Rituximab therapy (antibody
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targeting CD20). 41 patients were included in the treatment population. The overall response rate was
18/41 (43.9%). The median duration of response, progression-free survival, and overall survival were: 4.7
months, 4.4 months, and 9.2 months, respectively. Common non-hematologic adverse events included
asthenia/fatigue (30%), nausea (23%), and diarrhea (20%). Grade 3-4 adverse events were reported in 23
patients (38%), the most frequent being hepatotoxicity (3%) and abdominal pain (3%). In this trial, there
was no patient cohort treated only with traditional chemotherapy (negative control) because all patients
were resistant to traditional treatments and received the ADC treatment. We interviewed the
corresponding author of the paper Dr. Marek Trněný, MD, CSc, Professor and Chairman, 1st Dept
Medicine, Charles University, General Hospital, Praha, Czech Republic. When asked his opinion about
the median overall survival rate for the non-ADC-treated patients, he responded: “Generally speaking,
their median overall survival is about one year, but some patients could reach long-term survival”. So,
Dr. Trněný indicates that for the patients they used for the Phase-II tests (with relapsed or refractory
diffuse large B-cell lymphoma who had previously received Rituximab therapy), the median overall
survival is about 1 year. This is slightly more than the 9.2 months seen for their patients treated with their
ADC drug, so the ADC did not appear to lengthen overall survival in this particular study. This example
shows the difficulty of determining whether a drug benefits a population whose prognosis is extremely
poor from the beginning of the study.
Results for Dendritic Cell Vaccines In the cancer vaccine field, the experiments typically move from pre-clinical testing (which
includes testing the drug against cancer cell lines in vitro, and testing xenograft mice in vivo) into human
clinical trials. But it is not clear exactly how much information is needed from the pre-clinical testing
before moving into clinical trials. For example, we identified the following paper: Choi et al., 2018,
Combination Treatment of Stereotactic Body Radiation Therapy and Immature Dendritic Cell
Vaccination for Augmentation of Local and Systemic Effects. Cancer Research and Treatment, 2018 Jun
6. doi: 10.4143/crt.2018.186. The authors investigated dendritic cell (DC) vaccines and methods for
improving the efficiency of priming the DCs with tumor antigens. DCs can be primed against tumor
antigens in vivo in the patient, or ex-vivo by mixing isolated DCs with tumor antigens outside the
body. The ex-vivo approach is used most often in clinical trials, but the in vivo method has the advantage
of being available even when no tumor biopsy tissue is available to do the ex-vivo priming. Ionizing
radiation has recently been tested as a method for facilitating in vivo DC antigen priming, but exactly how
the radiation works to prime the DC cells is not clear. The radiation might help release tumor associated
antigens from the tumor, or it might increase the release of damage-associated molecular patterns
(DAMPs) (such as heat shock proteins) from dying tumor cells. In the Choi et al., 2018 study, the authors
investigated the use of stereotactic body radiation therapy (SBRT) as a method for facilitating the
presentation of tumor-associated antigens (TAA) to immature dendritic cells (iDCs). They tested their
method on mouse xenograft models of CT-26 colon carcinoma with 3 groups of mice: 1) radiation
therapy alone, 2) intra-tumor injection of DCs electroporated with tumor antigens, or 3) the combination
treatment. The data showed that the radiation method achieved the best DC priming and T-cell activation
compared to other priming methods, and that mouse survival was highest when using the combination
treatment. The authors conclude that clinical trials are warranted. We interviewed the corresponding
author on the paper: Dr. Chul Won Choi, MD, Department of Radiation Oncology, Dongnam Institute of
Radiological & Medical Sciences, Busan, Korea. When asked his opinion about whether it will be
necessary to more deeply understand the mechanism of how the radiation is facilitating the DC antigen
presentation process before proceeding to clinical trials, he responded: “Actually, I don't think so. There
are already many suggested mechanisms for how radiation enhances immune reactions. However, doing a
study on the ratio of apoptosis [programmed cell death] to necrosis [generalized cell death] after
irradiation would be interesting. Knowing this ratio would be helpful for determining the dose of
radiation, or for enhancing efficacy”. When asked whether his team was moving forward with clinical
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trials, he responded: “No. There are many limitations to moving to clinical trials including financial,
administrative, and legal issues. So, we won’t be going to the next step”. So, Dr. Choi thinks that it likely
is not necessary to obtain a full understanding of exactly how their radiation method works to prime DC
cells before proceeding to clinical trials, but that his lab is not moving forward due to financial,
administrative, legal, and scientific reasons.
As mentioned previously, for some of the clinical trials published in the literature, it was not clear
how the patient prognoses for patients receiving the cancer vaccine fared relative to untreated patients, or
to patients treated with traditional chemotherapy, because all patients receiving cancer vaccines have
received previous therapies and have relapsed/recurring cancers. For example, we identified the following
paper: Liau et al., 2018, First results on survival from a large Phase 3 clinical trial of an autologous
dendritic cell vaccine in newly diagnosed glioblastoma. Journal of Translational Medicine, 2018 May 29;
16(1): 142. This paper showed the results of a Phase-III trial of 331 patients with glioblastoma. The
standard therapy for glioblastomas is surgery, radiotherapy, and oral chemotherapy temozolomide. This
study evaluated the addition of an autologous tumor lysate-pulsed dendritic cell vaccine (DCVax®-L) to
standard therapy for newly diagnosed glioblastoma patients. After surgery and chemo-radiotherapy,
patients were randomly assigned to two groups: 1) chemo + DC vaccine (232 patients), or 2) chemo +
placebo (99 patients). However, if the patient’s cancer recurred, the patient was allowed to receive the DC
vaccine regardless of the initial group assignment. So, because of this “cross-over design”, nearly 90% of
the patients received the DC vaccine, and patient survival relative to a placebo could not be determined.
The median overall survival was 34.7 months, with a 3-year survival of 46.4%. We interviewed the
corresponding author on the paper: Dr. Linda M. Liau, MD, of the University of California Los Angeles
(UCLA) David Geffen School of Medicine & Jonsson Comprehensive Cancer Center, Los Angeles, CA.
When asked whether the median survival of 34.7 months was significantly better than the placebo group,
she responded: “Yes, the median overall survival for the entire intent-to-treat (ITT) population does seem
longer than the normal prognosis for glioblastoma patients based on historical controls” So, Dr. Liau
believes the average survival for the patients receiving her dendritic cell vaccine is longer than patients
not receiving it. Because most of the patients in her cross-over study received the DC vaccine, we must
rely on "historical data" for the untreated patients.
One trend observed in the literature is the use of combination cancer vaccines. Research teams
that had previously investigated single cancer vaccines were now testing combinations. And teams that
had previously tested combinations were now expanding the combinations to other types of cancer. As an
example, DC vaccines are being combined with checkpoint inhibitor vaccines. Checkpoint vaccines are
used to over-ride the immuno-suppression caused by the tumor cell interacting with the immune system
(typically DCs and T-cells). Three checkpoint targets came up repeatedly in our review: PD-1, PD-L1,
and CTLA-4. But given their importance, it makes sense to identify new checkpoint receptors as vaccine
targets. An interesting system was recently established using tumor “exosomes” (membrane vesicles) to
identify checkpoint inhibitors: Ning et al., 2018, Tumor exosomes block dendritic cells maturation to
decrease the T cell immune response. Immunology Letters, 2018 Jul; 199: 36-43. In this study, the authors
developed a system for determining whether exosomes produced by two particular types of cancer (LLC
Lewis lung carcinoma or 4T1 breast cancer) contribute to DC suppression. They found that exosomes
from these tumors indeed blocked the differentiation of myeloid precursor cells into DC cells, and
inhibited the migration and maturation of DCs. In addition, the inhibitory response was partially blocked
by treating with anti-PD-L1 antibody, suggesting this PD-L1 checkpoint inhibition is important to the
inhibition. We interviewed the corresponding author of the paper: Dr. Chunjian Qi, MD, PhD,
Professor and Director, Medical Research Center, The Affiliated Changzhou No.2 People's Hospital of
Nanjing Medical University, Changzhou, China. When asked now that he had set up the exosome system
for studying the inhibition process, whether he intends to investigate other potential blockers of the DC
activation besides PD-L1, he responded: “While PD-L1 antibody worked well, other blockers were not
investigated in this exosome system”. So, Dr. Qi indicated that they have not yet investigated any other
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checkpoint blockers (such as CTLA-4), so the latter could in theory also be involved in the inhibition
process.
An example of a new therapy that could in theory be combined with another to make a
combination is the following paper: Benitez-Ribas et al., 2018, Immune Response Generated With the
Administration of Autologous Dendritic Cells Pulsed With an Allogenic Tumoral Cell-Lines Lysate in
Patients With Newly Diagnosed Diffuse Intrinsic Pontine Glioma. Frontiers in Oncology, 2018 Apr 26;
8: 127. This was a Phase-Ib clinical trial of 9 patients with diffuse intrinsic pontine glioma (DIPG), a
lethal brainstem tumor in children. The authors tested autologous dendritic cell vaccines (ADCVs) pulsed
with allogeneic tumor cell-line lysates in newly diagnosed patients following radiation therapy. The DCs
were prepared from monocytes obtained by leukapheresis. The authors found that their pulsing procedure
boosted non-specific immune responses (KLH) in 9 of 9 patients, and it boosted specific anti-tumor
immune responses in 8 of 9 patients, in both PBMCs and T-lymphocytes isolated from CSF. We
interviewed one of the two corresponding authors on the paper: Dr. Andrés Morales La Madrid, MD,
Unidad de Neuro Oncología Pediátrica, Servicio de Oncología y Hematología Pediátrica, Hospital St Joan
de Déu, Passeig St Joan de Déu, Barcelona, Spain. When asked his opinion whether his pulsed dendritic
cell vaccine approach might be promising for use with other types of immunotherapies (especially
combined with checkpoint vaccines), he responded: “Based on the unpublished data from our lab we are
considering combining our DC vaccines with CTLA-4 inhibitors”. So, indeed he agreed with our
assessment that his DC vaccine approach for childhood glioma tumors might work better when combined
with a checkpoint vaccine (in his case combined with anti-CTLA-4).
For DC vaccines, using the ex vivo priming method usually involves mixing immature DC cells
with a tumor lysate. But when priming the DC cells in vivo in a patient, it is not clear how the DC cells
are primed. One example of this is the article: Garzon-Muvdi et al., 2018, Dendritic cell activation
enhances anti-PD-1 mediated immunotherapy against glioblastoma. Oncotarget, 2018 Apr 17; 9(29):
20681-20697. Glioblastoma (GBM) tumors strongly suppress the immune system. Checkpoint blockage
vaccines (such as antibodies against PD-1) might be useful for overcoming the blockade, but some
experiments suggest the checkpoint approach may not be sufficient by itself. The authors investigated the
activation of DC cells as a supplement to anti-PD-1 therapy in mice. Their data shows that activating
DCs by stimulating the TLR3 receptor with poly(I:C) enhances the PD-1 anti-tumor response, and
increases survival in mouse glioblastoma models. DC-depletion experiments showed that DCs are
required for the anti-tumor response. We interviewed the corresponding author for the paper: Dr.
Michael Lim, MD, Professor of Neurosurgery, Oncology, Radiation Oncology, Otolaryngology, and
Institute of NanoBiotechnology, Director of the Brain Tumor Immunotherapy Program, Director of the
Metastatic Brain Tumor Center, Johns Hopkins University School of Medicine, Baltimore, MD. When
asked about moving forward with clinical trials and whether he plans on using poly(I:C) to activate the
patient’s DC cells, he responded: “Yes, we are considering using polyIC”. So, Dr. Lim believes that
activating the toll-like receptor-3 TLR-3 using poly(I:C) should work in human patients, and can
supplement his anti-PD-1 therapy.
Results for TIL Vaccines
As mentioned previously, our review of the literature indicated that using combinations of
vaccines is a strong trend in the cancer vaccine field. An example of this using tumor-infiltrating
lymphocyte (TIL) vaccines is: Arias-Pulido et al., 2018, The combined presence of CD20 + B cells and
PD-L1+ tumor-infiltrating lymphocytes in inflammatory breast cancer is prognostic of improved patient
outcome. Breast Cancer Research and Treatment, 2018 June 1. doi: 10.1007/s10549-018-4834-7. In this
paper, the authors measured the levels of proteins PD-L1 (checkpoint inhibitor) and CD20 (tumor marker)
in 221 biopsies of patients with inflammatory breast cancer (IBC) as potential biomarkers of patient
outcomes. Their data showed that the combination of high levels of CD20-positive TILs plus high levels
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of PD-L1-positive TILs correlates with patient disease-free survival. We interviewed the corresponding
author for the paper Anonymous, a cancer vaccine researcher in the Departments of Microbiology and
Immunology, Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH.
When asked his opinion whether there are mouse xenograft models for inflammatory breast cancer (IBC),
and if so, whether he has tested checkpoint therapy in that model, he responded: “Yes, actually I have a
few IBC [inflammatory breast cancer] cell line models that are being used to evaluate small molecule
inhibitors. And I’m developing humanized PDX [patient-derived xenograft] models, but we have not used
these [PDX] models yet, mainly due to money issues, and the issues of autologous vs. allogeneic immune
cells used for those experiments”. Thus, the cancer vaccine researcher agrees with our assessment that
anti-PD-1 or anti-PD-L1 antibody checkpoint therapy might help supplement his TIL therapy for breast
cancer, and he would like to test the therapy combination in mouse models for breast cancer once money
is not an issue.
When using TIL vaccines, we found that some researchers isolated and expanded in vitro specific
TILs that target a particular tumor antigen, while other researchers attempted to amplify all TILs isolated
from a patient’s tumor (which presumably can target multiple tumor antigens). But is was not clear to us
which approach is best. To shed light on this issue, we interviewed Dr. Emese Zsiros, of the Department
of Gynecologic Oncology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, who is a
corresponding author on the paper: Mayor et al., 2018, Adoptive cell transfer using autologous tumor
infiltrating lymphocytes in gynecologic malignancies. Gynecologic Oncology, 2018 May 23. pii: S0090-
8258(18)30920-X. The paper provides an overview of the current clinical results, risks, challenges, and
future applications of TIL-based therapy in gynecologic malignancies. When asked her opinion about
treating gynecologic tumors and whether the best results are obtained by selecting the TILs against a
particular target antigen, or by attempting to amplify all TILs present in a tumor biopsy, she replied: “This
is a tough question. It would be easier to just target one specific universal antigen and engineer cells
against that antigen, but unfortunately we don’t have such a universal antigen expressed by every ovarian
cancer cell in every patient and not expressed by normal cells in the body. There are T cells engineered
against target NY-ESO for example, but only about 20-30% of ovarian cancer patients express that.
Using a diverse group of TILs isolated from tumor tissue is more attractive as they are polyclonal,
however there are many patients where there are essentially no T cells in the tumor microenvironment,
which makes this approach challenging as well. Also resecting tumor tissue from recurrent disease deep
inside the pelvis and or other areas/organs is often challenging and risky in ovarian cancer patients. In an
ideal world, finding a good neoantigen target that is specific would be the best, and just target that”. So,
Dr. Zsiros indicates that each of the two main TIL methods (isolating TILs that target one antigen, or
isolating polyclonal TILs from a resected sample that target multiple antigens) have their advantages and
problems. Using the first method fails to treat tumor cells that lack the target. A universal target does not
exist for ovarian tumors, if it did that would be the way to go. Using the second method with polyclonal
TILs is better as it kills a larger variety of tumor cells, but TILs are not always present and isolatable from
a tumor, and resecting deep ovarian tumors has its problems.
For breast cancer tumors, obtaining tumor samples via core needle biopsy is increasingly
common. But for cancer vaccines, it is unclear whether the biopsy sample is immunologically equal to
the main tumor with respect to TIL cells. One paper that addresses this problem directly is: Cha et al.,
2018, Comparison of tumor-infiltrating lymphocytes of breast cancer in core needle biopsies and resected
specimens: a retrospective analysis. Breast Cancer Research and Treatment, 2018 June 5. doi:
10.1007/s10549-018-4842-7. The authors investigated whether the TIL scores in core needle biopsies
(CNBs) taken from patients with advanced breast cancer are immunologically representative of those
taken from resected specimens. They analyzed 220 matched pairs of CNBs versus their resected
counterparts, scoring stromal TILs on slides stained with H&E. The authors concluded that more than
five CNB cores accurately predicts the TIL score of the entire tumor. We interviewed the first author on
the paper (whose name was forwarded to us from the corresponding author): Dr. Yoon Jin Cha,
Department of Surgery, Gangnam Severance Hospital, Yonsei University College of Medicine, 211
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Eonju-ro, Seoul, Republic of Korea. When asked whether she is aware of any study comparing the
anti-tumor therapeutic activity of TILs amplified from core needle biopsies versus TILs prepared from
resected specimens, she responded: “In general, high TILs in breast cancer are known to be a positive
predictive marker of neoadjuvant chemotherapy in HER2 and TNBC tumors. Among the TILs, CD8+ T-
cells may be the most important for the anti-tumor effect, and are known to be elevated in HER2 and
TNBC tumors, which may have association with improved treatment response in those subtypes. With
respect to your question about whether we are aware of any study comparing the anti-tumor therapeutic
activity of TILs amplified from core needle biopsies versus TILs prepared from resected specimens, I am
not aware of any. I think that to compare the anti-tumor activity of TILs in biopsies vs resections, each
subpopulation of TILs (such as CD8, CD4, FOXP3) should be measured via IHC. And the regional
heterogeneity of immune microenvironment should be considered”. So, Dr. Cha indicates that, in general,
high levels of TIL cells present in a breast cancer tumor predict a good prognosis. She also notes that
among the various types of cells present in the TIL population, the presence of high levels of CD8-
positive cells (cytotoxic T-cells) have the most important anti-tumor effect. She was not aware of any
study attempting to determine whether TILs isolated from breast cancer core needle biopsies are as
effective as those isolated from resected specimens, so that can be a future experiment.
Several studies in our review of the literature indicated that therapies with a high number of TIL
cells provides a better prognosis for the patient. A paper related to this topic is: Huang et al., 2018,
Prognostic impact of tumor infiltrating lymphocytes on patients with metastatic urothelial carcinoma
receiving platinum based chemotherapy. Scientific Reports, 2018 May 10; 8(1): 7485. The authors
investigated the prognostic role of TIL levels on patient survival for metastatic urothelial carcinoma
(mUC). The patients also received standard platinum-based chemotherapy. They analyzed 259 mUC
patients, of which 179 (69%) had intense (high) TILs, and 80 (31%) had non-intense (low) TILs. The
median overall survival was 15.7 months for the intense TIL group versus 6.7 months for the non-intense
group (p < 0.001). The authors conclude that assaying TIL staining intensity (numbers) for mUC patients
is clinically useful for patient risk stratification and counseling. We interviewed the corresponding author
for the paper: Anonymous, Department of Hematology-Oncology, Kaohsiung Chang Gung Memorial
Hospital, Kaohsiung City, Taiwan. When asked whether their data showing that patients with metastatic
urothelial cancer with intense TIL staining have a longer overall survival than those with low intense
staining could be extended to hypothesize that treating mUC patients with high TIL numbers (perfusing a
high number) should be superior than treating with low numbers, he replied: “You are right. The
oncologic outcomes of treating mUC [metastatic urothelial carcinoma] patients with high TIL numbers
are superior than those of treating with low numbers. The immune micro-environment is essential in the
treatment”. Thus, researchers have taken the general finding that high TIL numbers in a tumor correlate
with good patient prognosis, and extended that finding to treat patients with a high number of TILs.
Another paper on the topic of high TIL numbers correlating with good patient prognosis is:
Aghajani et al., 2018, Predictive relevance of programmed cell death protein 1 and tumor-infiltrating
lymphocyte expression in papillary thyroid cancer. Surgery, 2018 Jan; 163(1): 130-136. In this paper, the
authors studied the levels of TIL density and the levels of PD-1 which is produced by some tumor cells
and binds to receptor PD-1 on T-cells to induce a strong inhibition of TILs that have migrated to the
tumor site. The authors investigated the predictive value of assaying PD-1 expression and TIL density in
75 patients with papillary thyroid tumors. Their data showed that PD-1 expression significantly
correlated with increased incidence of lymphovascular invasion (P = .038), extrathyroidal extension
(P = .026), and concurrent lymphocytic thyroiditis (P = .003). In the TIL population, a low presence of
CD8+ and CD3+ (cytotoxic T-cells) correlated with a significantly higher incidence of lymph node
metastasis (P = .042) and extrathyroidal extension (P = .015). A high density of CD8+ TILs was
significantly associated with favorable disease-free survival (P = .017), and the shortest patient survivals
occurred in patients with high PD-1, and low CD8. We interviewed the corresponding author on the
paper: Anonymous, Thyroid Cancer Group, Ingham Institute for Applied Medical Research, Liverpool,
NSW, Australia; and the School of Medicine, Western Sydney University, Campbelltown, NSW,
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Australia. When asked “based on the findings of your paper that patients with papillary thyroid cancer
with high PD-1 expression and low CD8+ cells in the tumors have poor prognosis, we assume it could be
hypothesized that treating such patients with a combination of a high number of TILs (containing CD8+
cells) and anti-PD-1 checkpoint therapy might benefit those patients?” She replied: “It is a possibility,
and there have been some studies investigating the potential of combining PD-1/PD-L1 targeted
immunotherapies with other treatments to increase CD8 T-cell populations. However, the combination
therapy has yet to be investigated in patients with thyroid cancer. So, she agreed that for her papillary
thyroid cancer patients with high PD-1 expression and low TIL CD8+ cells (and very poor prognosis),
those patients might benefit from a combination therapy of a high number of TILs (containing CD8+
cells) and anti-PD-1 checkpoint therapy, although to her knowledge that experiment has not yet been
done.
With respect to the topic of TIL numbers versus patient prognosis, some scientists have
observed a difference between a high number of infiltrating neutrophils versus a high number of CD8+
cytotoxic killer cells. An example is the paper: Liu et al., 2018, The prognostic values of tumor-
infiltrating neutrophils, lymphocytes and neutrophil/lymphocyte rates in bladder urothelial cancer.
Pathology Research and Practice, 2018 May 20. pii: S0344-0338(18)30352-2. In this paper, the authors
investigated the roles of tumor-infiltrating neutrophils (TINs), tumor-infiltrating lymphocytes (TILs), the
neutrophils/lymphocytes ratio (NLR), and clinical outcomes in patients with bladder cancer (BC). They
analyzed 102 bladder cancer patients. Immunohistochemistry was used with CD66b antibodies to score
neutrophils, and with CD8 antibodies to score lymphocytes. Their results indicated that high TINs and
high NLR ratios associated with poor overall patient survival, while higher TILs correlated with longer
survivals (P < 0.01). We interviewed the corresponding author on the article: Dr. Erlin Sun, Department
of Urology, Tianjin Institute of Urology, The 2nd Hospital of Tianjin Medical University, Tianjin, China.
When asked his opinion of why the high tumor-infiltrating neutrophil count correlated with poor patient
outcome, while high TILs correlate with better patient prognosis, he replied: “We know that neutrophils
can be polarized into either an anti-tumoral (N1) or a pro-tumoral (N2) phenotype, so they show different
functions. N1 neutrophils are anti-tumoral effector cells by inducing cytotoxicity, mediating tumor
rejection and anti-tumoral immune memory. In contrast, N2 phenotype neutrophils support tumor
progression by promoting angiogenesis, invasion, metastasis and immunosuppression. According to the
results of our study, we suspect that tumor-infiltrating neutrophils have pro-carcinogenic [N2 phenotype]
effects on tumor progression. However, tumor-infiltrating CD8+ lymphocytes are found to be favorable
prognostic factors in our study, which may play a role in tumor suppression by immune process. Our
results are just a clinical retrospective analysis, the mechanism still need to be researched”. So, Dr. Sun
thinks that the reason a high tumor-infiltrating neutrophil count correlates with poor patient prognosis is
that the infiltrating neutrophils are of a N2 phenotype that is pro-tumorigenic. N2 neutrophils promote
angiogenesis, invasion, metastasis, and immunosuppression. So, it will be important in future studies to
assay for exactly which types of immune cells have migrated to the tumor site.
Results for CAR Vaccines A problem noted throughout our Lit Review is the induction of side-effects caused by the
vaccine. In the case of CAR vaccines, the side-effects can be caused by the presence of target antigen in
normal tissues (so the T-cells target and kill those normal cells). An example of this is the paper:
Richman et al., 2018, High-Affinity GD2-Specific CAR T Cells Induce Fatal Encephalitis in a Preclinical
Neuroblastoma Model, Cancer Immunology Research, 2018 Jan; 6(1): 36-46. In this article, the authors
studied neuroblastoma xenograft mouse models with a vaccine containing GD2-CAR T-cells. The CARs
showed enhanced anti-tumor activity, but in some cases the treatment caused death of the mice. The
authors observed brain T-cell infiltration and proliferation (which seems necessary for killing the tumor
cells), but the T-cells may have also targeted nearby GD2 in normal brain cells. We interviewed the
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corresponding author for the paper: Dr. Michael C. Milone, Center for Cellular Immunotherapies,
Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania. When asked
his opinion whether targeting GD2 in normal cells can be avoided in human patients, he replied: “…The
T cell activity in the brain is due to targeting low level GD2 expression on neurons and glial cells. While
some scientists believe it is possible to design a CAR T-cell therapy that can distinguish the generally
higher expression in tumors compared to the normal expression, I think this will be challenging with
current technology”. So, Dr. Milone agrees that the sometimes fatal encephalitis he observes in his mouse
models treated with GD2-CAR cells likely results from the targeting of GD2 in normal neurons and glial
cells expressing low levels of GD2. He believes it will be challenging to design a CAR to distinguish the
high GD2 expressors from the low expressors. So, more research should be done identifying antigens
almost exclusively expressed in the tumors, if possible.
Another example paper dealing with CAR-induced side-effects is Locke et al., 2017, Phase 1
Results of ZUMA-1: A Multicenter Study of KTE-C19 Anti-CD19 CAR T Cell Therapy in Refractory
Aggressive Lymphoma. Molecular Therapy, 2017 Jan 4; 25(1): 285-295. In this study, the authors
designed CAR KTE-C19, an autologous CAR T-cell therapy targeting CD19 that also uses CD3-zeta and
CD28 as co-stimulators to treat patients with refractory B-cell leukemia. The CAR was was used to treat
7 patients. 1/7 patients (14%) experienced dose-limiting toxicity of grade-4 cytokine release syndrome
(CRS), 1/7 patients (14%) showed grade >3 CRS, and 4/7 patients (57%) showed neurotoxicity. All
>grade-3 events resolved within 1 month. 3/7 patients showed clinical responses (stabilizations) at 12
months. To get an idea of the main cause of the side-effects, we interviewed the corresponding author for
the paper: Dr. Frederick L. Locke, MD, Department of Blood and Marrow Transplantation, Moffitt
Cancer Center, Tampa, FL. When asked his opinion on the cause of the neurotoxicity observed in 4 of
your 7 (57%) phase-I patients, he stated: “More and more evidence suggests that there is breakdown of
the blood brain barrier, so the CAR T-cells get into the CSF where they continue to secrete cytokines.
This likely leads to endothelial damage and dysfunction, which appears to be the main driver of CNS
toxicity”. So, Dr. Locke indicates that the evidence from his lab suggests the neurotoxicity observed with
his KTE-C19 CAR therapy is caused by a breakdown of the blood brain barrier (BBB), allowing CAR
cells to enter the cerebrospinal fluid (CSF), and in a deteriorating cycle of events the CAR T-cells
continue to secrete cytokines in the CSF that causes endothelial cell damage. Thus, the side-effects are not
only caused by a targeting of a specific antigen in normal cells, it is also caused by the continued elevated
production of cytokines by the T-cells.
The most frequently observed side-effect is cytokine release syndrome (CRS). Thankfully, in
most cases, the CRS was manageable by treating with corticosteroids and IL-6-receptor blocking
antibodies. In order to shed light on how cancer vaccine treatments can cause CRS, we interviewed the
corresponding author on a paper where CRS was observed: Young et al., 2018, Activity of Anti-CD19
Chimeric Antigen Receptor T Cells Against B Cell Lymphoma Is Enhanced by Antibody-Targeted
Interferon-Alpha. Journal of Interferon and Cytokine Research, 2018 Jun; 38(6): 239-254. The
corresponding author is: Dr. John M. Timmerman, Division of Hematology & Oncology, Department
of Medicine, Center for Health Sciences, University of California at Los Angeles, Los Angeles, CA. In
this paper, the authors investigated methods for lengthening the survival of CD19-CARs in patients with
B-cell lymphomas. Because interferons (IFNs) have the ability to promote T-cell activation and survival,
the authors tested whether antibody-targeted IFN therapy could enhance their CAR therapy. They
produced a new type of CAR anti-CD20-IFN, containing an antibody-like portion against the CD20
lymphoma target fused with a potent type-1 IFN isoform alpha14 (α14). The combination approach was
found to enhance lymphoma cell killing in vitro. Pre-treatment of the lymphoma cell lines with the fusion
peptide (anti-CD20-hIFNα14) markedly increased cytokine production by the subsequently added CARs,
enhancing several CAR activities, but it was unclear to us whether this novel approach might increase the
incidence of cytokine release syndrome. When asked whether his new anti-CD20-hIFNα14 treatment
might cause increased cytokine release syndrome, Dr. Timmerman replied: “Maybe in some patients. But
there are many patients that don't have a clinical response [to the CD19-CAR] or much CRS, so if we
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knew how to predict those patients, adding the [anti-CD20-hIFNα14] fusion protein might help them”.
So, Dr. Timmerman agreed with us that his new drug could indeed increase the incidence of cytokine
release syndrome, but that the drug is strongly needed to treat the lymphoma patients that do not respond
to CD19-CARs, as it targets a different antigen (CD20) on the lymphoma cells, so this warrants its use.
Sometimes tumor location is important. For example, solid tumors are difficult to treat with
cancer vaccines due to their location and general inaccessibility. Over the past decade, the use of CAR
cells has led to strong improvements in patients with hematopoietic malignancies which are readily
treated by systemic infusions on of the CAR cells. But CAR treatment of solid tumors is hindered by
challenges inherent to an organized tumor mass, such as abnormal vasculature, migration through a dense
stroma, and an elevated tumor interstitial pressure (IFP). Some scientists are trying to overcome these
problems by performing a localized delivery of the CARs directly to the tumor. An example of this is the
paper: Hardaway et al., 2018, Regional Infusion of Chimeric Antigen Receptor T Cells to Overcome
Barriers for Solid Tumor Immunotherapy. Journal of Vascular and Interventional Radiology, 2018 Jul;
29(7): 1017-1021. The authors take advantage of the fact that hepatic tumors derive their blood supply
from the hepatic arterial circulation (where the scientists deliver CARs), while normal hepatocytes mainly
subsist off the portal circulation (not encountered by the CARs). This regional delivery approach has
already been used with chemotherapeutic, radiotherapeutic, and chemoembolic agents for liver
tumors. The regional approach has also been used for the treatment of of hepatic and pancreatic
malignancies with dendritic cells, macrophages, or lymphokine-activated killer cells (LAKs). We
interviewed the corresponding author for the paper: Dr. Steven C. Katz, MD, FACS, Associate
Professor of Surgery, Director, Complex General Surgical Oncology Fellowship, Director, Office of
Therapeutic Development, Roger Williams Medical Center, Providence, Rhode Island. When asked his
opinion about whether his regional CAR delivery method would not only treat the cancer but help
diminish the adverse side-effects, he replied: “We believe the overall therapeutic index would be
enhanced, in general, for regionally infused products”. So, Dr. Katz agreed that his regional method for
delivering CAR T-cells to solid tumors not only reduces the tumors better, it also decreases the adverse
side-effects.
With respect to CAR vaccines, some researchers are working on new methods for delivering the
CAR receptor gene to the T-cells without using lentiviruses (non-lentiviral delivery methods). The
lentiviruses tend to integrate at random sites and can be harmful. A new technique delivers the RNA
encoding the CAR receptor directly to the T-cells, as seen in the paper: Svoboda et al., 2018, Non-viral
RNA chimeric antigen receptor modified T cells in patients with Hodgkin lymphoma. Blood, 2018 Jun
20. pii: blood-2018-03-837609. The authors treated 4-5 patients with classical Hodgkin lymphoma (cHL)
using CAR T-cells. To limit potential toxicities, they used non-viral RNA CART19 cells, which the
authors expected to express the CAR receptor protein only for a few days off the delivered RNA, as
opposed to CARs generated by viral vector transduction which expand in vivo and retain CAR expression
via the integrated DNA. Their results showed no severe toxicities. To our knowledge, this is the first
CART19 clinical trial to use non-viral RNA gene delivery. But it was unclear to us how efficient the
RNA technique was relative to the highly efficient lentivirus technique, so we interviewed the
corresponding author on the paper: Dr. Jakub Svoboda, Lymphoma Program, Abramson Cancer Center,
University of Pennsylvania, Philadelphia, PA. When asked what percent of the patient’s T-cells can be
treated with the RNA technique versus treatment with a lentivirus encoding the CAR gene, he replied:
“That is a good question, but difficult to answer since every patient is different. [In our study] the number
of infused modified RNA CART19 cells varied (the dose was based on weight, the protocol allowed for a
range). These cells [RNA-treated CAR cells] are transient (last few days, do not expand) and they likely
represent only a tiny portion of the lymphocytes in relation to the total number in the human body (the
total number of lymphocytes in the human body is estimated to be about 2x1012). For the lentivirus
transduced CART19 cells, these tend to expand in vivo, but the expansion varies from patient to patient,
but again - likely a tiny portion”. So, Dr. Svoboda indicated that it is difficult to determine the percent of
T-cells transduced with his RNA technique to deliver the CAR gene versus using a lentivirus, but in any
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case, the end numbers vary for each patient depending on the extent of CAR expansion, not just based on
the percent transfected.
Results for Checkpoint Inhibitor Treatments
One of the recent trends in the checkpoint vaccine field is uncovering various ways that some
tumors are resistant to checkpoint therapy. For example, an exciting find in 2018 was the discovery
that a high level of TGFβ hormone in the tumor micro-environment acts as a primary mechanism of
immune evasion for tumor cells (Tauriello et al., TGFβ drives immune evasion in genetically
reconstituted colon cancer metastasis, Nature, 2018 Feb 22; 554: 538-568). In order to gain information
on the feasibility of using a combination of a checkpoint therapy with anti-TGFβ antibody, and
determining how TGFβ levels might be assayed in patients, we interviewed the first author on the article
(whose name was provided by the corresponding author): Dr. Daniele Tauriello, Institute for Research in
Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.
When asked her opinion of whether a clinical trial might be feasible combining a checkpoint inhibitor
vaccine with anti-TGFβ antibody, she replied: “We think that, at least in CRCs [colon cancer
metastases], high levels of TGFβ prevent or strongly diminish a full activation of T cells. Furthermore, T
cell infiltration is low, which could be a direct result of T cell dysfunction, but might also be a separate
mechanism by which TGFβ affects immune evasion. If these are the two main ways in which high TGFβ
levels suppress anti-tumour immunity, then inhibition of the TGFβ pathway (for example with TGFBRI
inhibitor Galunisertib), should lead to full activation of T cells….. and a combined inhibition of stromal
TGFβ signalling with blockade of the PD-1/PD-L1 checkpoint could be an effective way to overcome
immune evasion in patients with advanced/metastatic CRC”. When further asked whether there is an
assay for clinicians to quantitate the levels of TGFβ in the tumor microenvironment (to predict which
patients might benefit from the combined therapy), she responded: “….in our lab's previous papers we
showed that high TGFβ mRNA levels strongly predict poor prognosis in stage I+II+III patients, so if
primary tumours could be removed by surgeons and analysed for TGFβ mRNA levels (or analyzed for
TGFβ-controlled gene expression levels), …we expect that the combined insight will lead to more power
to clinically intervene”. So, Dr. Tauriello indicated that the way to measure TGFβ levels in patients
would be for the surgeons to remove the primary tumors, and then for lab personnel to assay for for TGF-
beta gene transcription levels (presumably using something like RT-PCR). The high TGFβ patients would
have a poorer prognosis but should respond to their dual therapy.
All cancer immuno-therapies have side-effects, and checkpoint inhibitor treatments are no
exception. But the presence of side-effects does not necessarily mean the drugs should be discontinued.
In most cases, the side-effects observed were mild and transient, and are likely far outweighed by the poor
prognosis of a relapsing cancer patient. To gain more insight on the topic of checkpoint inhibitor side-
effects, we interviewed an expert on liver injuries induced by checkpoint inhibitor treatments, Dr.
Eleonora DeMartin, Centre Hépatobiliaire, Hôpital Paul Brousse, Groupe Hospitalier Paris Sud, DHU
Hepatinov, Villejuif, France. Dr. DeMartin’s contact information was provided by the corresponding
author of the paper: De Martin et al., 2018, Characterization of liver injury induced by cancer
immunotherapy using immune checkpoint inhibitors, Journal of Hepatology, 2018 Jun; 68(6): 1181-1190.
When asked her opinion of whether the benefits of checkpoint inhibitor therapy outweigh the side-effects
caused by the treatments, she replied: “I agree that most of the immune-mediated hepatitis side-effects
provide a far better prognosis than the prognosis from cancer relapse/progression. Liver injury induced by
cancer immunotherapy either improves spontaneously, or it responds to corticosteroid therapy in most of
the patients. Interestingly, it seems that patients who develop immune-related adverse-effects (iRAEs)
better respond to therapy. However this finding needs to be confirmed”. When asked whether there is any
way for a clinician to predict which patients are more likely to develop liver injuries following checkpoint
therapy, she replied: “No, unfortunately we haven't been able to identify predictive factors for hepatic
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IRAEs. We are running a multidisciplinary study now in order to answer this question”. When asked
whether she thinks that autoimmune diseases resulting from checkpoint inhibitors are severe enough and
common enough to prohibit inhibitor usage, she replied: “The answer is no. They remain a rare
complication, and in most cases they are not severe. Considering the revolutionary results of cancer
immunotherapy I encourage its use”. So, Dr. DeMartin, indicated that in the case of her patients treated
with checkpoint therapies, the side-effects are minor or rare, and are less important than attempting to
save the patient’s life from a relapsing cancer.
Continuing on the topic of side-effects caused by checkpoint therapies, we interviewed Dr.
Michael A. Postow, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New
York. Dr. Postow was corresponding author on: Postow MA, Sidlow R, Hellmann MD (2018) Immune-
Related Adverse Events Associated with Immune Checkpoint Blockade. New England Journal of
Medicine, 2018 Jan 11; 378(2): 158-168. When asked his opinion about whether the side-effects are
outweighed by the potential benefits of the checkpoint therapy, he replied: “I think the benefits
dramatically outweigh the possibility of side-effects. Untreated metastatic cancer invariably leads to
death at some point. Immunotherapies offer patients the hope that they can keep their cancer under
control for a long time if they respond well. This is an amazing potential benefit and well worth the
possibility of side-effects. And even if side-effects occur, they can be well managed and do not usually
lead to permanent disability. The side-effects usually resolve within weeks to months”. When asked
whether there is any way for physician’s to determine which patients will develop side-effects, he
responded: “Unfortunately we do not really know. There are many research programs going on to
identify predictive factors that are associated with immunotherapy side-effects. It may have to do with
germline genetics, or with other “host” immunologic factors. Some people think that patients with less
heavy of a burden of cancer are more likely to have side effects, perhaps because these patients with
lower tumor volume are less immunosuppressed”. And when asked his opinion about whether there is a
subset of patients that should absolutely not receive checkpoint therapy, such as immunocompromised
patients or patients on immunosuppressant drugs, he replied” Although efficacy may be a little lower in
patients on immunosuppressants or otherwise immunocompromised, since these patients have been
shown to benefit from immunotherapy in some situations, I think it is reasonable to try immunotherapy
when no other good cancer treatments are available”. Thus, Dr. Postow is a strong advocate of attempting
to use immunotherapies on patients with otherwise very poor prognoses, even if some side-effects
develop.
One serious side effect of checkpoint inhibitor therapy is the occasional development of T-cell
tumors. The point of checkpoint therapy is to activate the patient’s inhibited T-cells, and sometimes
tumors develop. A paper covering this topic is: Ludin and Zon, 2017, Cancer immunotherapy: The dark
side of PD-1 receptor inhibition. Nature, 2017 Dec 7; 552(7683): 41-42. doi: 10.1038/nature24759.
We interviewed Dr. Aya Ludin Tal, Postdoctoral Fellow, Zon Lab, Harvard Department of Stem Cell
and Regenerative Biology, Harvard Stem Cell Institute, Harvard University, Cambridge, MA. Dr. Tal’s
contact information was provided by Dr. Zon, the corresponding author on the paper. When asked
whether there is any way that physician’s can determine which patients will develop T-cell tumors, she
replied: “…. In some cases, the patient already has a T-cell tumor, [and in these cases] various options of
treatment should be considered. ….If their T cells are cancerous, it might not be a good idea to expand
this population of cancer cells by driving them into proliferation using PD-1. PD-1 inhibition is not yet
used in hospitals with patients with T cell-based cancers, but since it is gaining interest in multiple types
of cancers, the authors warn against possible side effect that is not seen in other types of cancer”. Their
paper also showed that anti-PD-1 activates different subsets of T-cells, so we asked her which types are
more effective for their patients. She replied: “Different subsets of T cells have different roles in fighting
or protecting cancer. Cytotoxic [CD8+] and helper cells [CD4+] help fight tumors, whereas regulatory T
cells [T-reg] can protect the tumors”. And when asked whether the overall risks of immunotherapy are
different or on par with other cancer treatments like radiation or surgery, she replied: Each treatment has
its own risks, so it’s hard to say. It also depends on the type of immunotherapy used, each has its own
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risk, such as the induction of autoimmune effects through CAR T-cell administration (uncontrolled T
cells). The risks of the different immunotherapies are still being investigated. However, anti PD-1 and
anti-CTLA-4 therapies have already been approved clinically for many types of cancers, suggesting that
the benefit for the patient is higher than the risk. The efficiency of treatment, whether it be
immunotherapy, surgery or irradiation is an important factor considered, and many times these treatments
are combined together”. Thus Dr. Tal indicated that checkpoint therapy is not yet used clinically for
patients with T-cell tumors (as it could further activate the tumors), but warns the current emphasis on
expanding checkpoint therapy to other types of cancers should consider the effects on T-cells. And with
respect to the overall risk, she pointed out that checkpoint therapies have already received FDA approval,
so a panel of experts have already determined that the benefits outweigh the risks.
An interesting recent finding in the checkpoint inhibitor field is the discovery that the gut
microbiome (the type and quantity of bacteria present in the gut) strongly affects the response to
checkpoint therapy. An example is the article: Gopalakrishnan et al., 2018, Gut microbiome modulates
response to anti-PD-1 immunotherapy in melanoma patients, Science, 2018 Jan 5: 359(6371): 97-103.
We interviewed the first author on this paper Dr. Vancheswaran Gopalakrishnan, Department of
Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Dr. Gopalakrishnan’s contact information was provided by the corresponding author on the paper. One of
the findings of the paper was that patients with a gut microbiome enriched for Ruminococcaceae family
bacteria respond better to anti-PD-1 therapy, so we asked Dr. Goplakrishnan whether they plan to move
forward with clinical trials by supplementing patient microbiomes with Ruminococcaceae microbes? He
replied: “We are planning a clinical trial to test the hypothesis that modulation of the gut microbiome will
enhance therapeutic responses. Several strategies will be used, including fecal microbiota transplant and
designer probiotics that enrich for favorable bacteria……. FMT [fecal microbiota transplants] have
already proven to be successful for treatment of Clostridium difficile infections, but there is limited data
for oncology [and FMTs]. In addition to the above, one may also consider lifestyle changes such as
dietary modifications to modulate/maintain the microbiome”. When asked how difficult it is to assay a
patient’s microbiome, he replied: “This can be done in several ways. The most commonly used approach
is called 16S rRNA sequencing. The 16S gene is a ubiquitous bacterial marker that has both conserved
and variable regions. The conserved regions act as targets for PCR-primers. The variable regions can be
amplified, sequenced and compared with reference databases to identify bacterial diversity and
composition. Another approach is whole genome shotgun sequencing. This gives greater resolution of
bacteria at the species level and also gives a sense of their functional capabilities. But sequencing takes
time, with a turnaround of approximately 1 month, so this is not yet feasible at a per-clinic basis. But this
is surely something that people are invested in”. Thus, Dr. Gopalakrishnan provided some very useful
information on: 1) how indeed they are moving forward to test their hypothesis that modifying the gut
microbiome affects the success of PD-1 therapy, 2) there are several different ways they plan to modify
the microbiome in patients (including fecal transplants and probiotics), and 3) the methods for assaying
species type and number in the biome include sequencing ribosomal RNAs, and performing
bioinformatics to determine the species type and abundance.
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CONCLUSIONS and RECOMMENDATIONS
Based on the research performed for this IQP project, our team has developed several conclusions
and recommendations. We focused on two main problems prevalent in the area of cancer vaccines: 1) the
fact that only a subset of patients respond to a particular therapy, and 2) the fact that most cancer vaccines
cause adverse side-effects. We emphasized new advances in the field for overcoming these problems.
Cancer Vaccine Non-Responding Patients
With respect to the topic of non-responding patients, our research indicates that tumors resistant
to cancer vaccine treatments occur for all types of cancer vaccines and for all types of cancers. These
tumors are non-responsive for a variety of reasons. Some of the most important reasons are discussed
below along with potential solutions:
1) Down-Regulation of the Target Antigen: The major mode of resistance of some tumors to immune
therapy is a loss of target antigen on the surface of the tumor cells. For reasons that are not yet
understood, in some cases a patient’s tumor stops making the target antigen, or lowers its expression.
When this occurs, a potential remedy is to follow the initial failed therapy with a different one that targets
another antigen, if available. This combination approach is most feasible for the lymphomas and
leukemia where multiple target antigens are already available. One of the best practices we observed in
our review of the cancer vaccine clinical trials was the constant monitoring of target antigen expression
on the tumor. This is easily done by using immunohistochemistry (IHC) to measure the levels of target
protein, or by using reverse transcriptase polymerase chain reaction (RT-PCR) to measure the levels of
target mRNAs. The best patient prognoses were observed for patients with tumors strongly expressing
the target antigen.
2) Tumor Heterogeneity: A recent discovery in the cancer field is that some tumors are not
homogeneous; they consist of regions that differ from each other. In some cases, portions of the tumor
may lack expression of the target antigen, so those cells will not be killed by the vaccine and will continue
growing. In other cases, different areas of a tumor express different neo-antigens (new proteins made by
a tumor caused by different DNA mutations over time). In these cases, different areas of the tumor are
genetically distinct from each other. Each has their own growth rates, metabolic pathways, and overall
aggression. In these cases, if it is possible to resect genetically different parts of the tumor without
harming the patient, perhaps different tumor regions can be identified with their corresponding antigens,
then the patient could be treated with a combination vaccine against the antigens of each section.
3) Immunosuppression Induced by the Tumor: In some cases, the patient’s tumor inactivates the
patient’s immune system, lowering removal of a cancer (or blocking a cancer vaccine). In some cases,
this inactivation occurs via checkpoint inhibition on nearby T-cells to keep them in check. This immuno-
suppression keeps the T-cell from killing the tumor. The discovery of key components of checkpoint
inhibition (including PD-1, PD-L1, CTLA-4) has in recent years allowed the use of antibodies against the
components to re-activate the patient’s immune system. This type of cancer “vaccine” has increased
exponentially in the past few years. A very recent 2018 discovery is the strong role of TGFβ in the tumor
microenvironment at inhibiting T-cells or DCs that have migrated to the tumor, and this finding opens up
the possibility of treating these resistant patients with anti-TGFβ antibodies, or with antibodies that block
TGFβ signaling.
4) Immunocompromised Patients: In some cases the patient is immunocompromised due to their pre-
treatment with chemotherapy (which destroys actively dividing cells in the body). In these cases, the
patient may lack the necessary immune components for killing the tumor. In the case of monovalent
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antibody treatments, the binding of the vaccine antibody to the tumor cell by itself does not kill the cell,
and other components of the immune system must recognize the bound antibody and help kill the cell. In
the case of bispecific antibodies designed to bind the target antigen on the tumor cell while also binding to
a T-cell to bring them together, an immunocompromised patient may lack a sufficient number of T-cells
to be recruited to the site. So, perhaps these patients could be treated with an ADC vaccine or a CAR T-
cell vaccine, which by themselves can kill a tumor cell.
5) Short Vaccine Half-Life: In some cases, the cancer vaccine was ineffective in a patient due to a short
half-life. This was especially a problem with passively administered antibody vaccines that are rapidly
cleared from the body. A recent trend with antibody vaccines is to encode the antibody genes in a
deliverable vector (such as a harmless virus), and deliver the vector to the patient’s bloodstream. The
DNA continues to express the antibody gene far longer than with a delivered protein antibody. The short
half-life of some CAR T-cell vaccines appears to have resulted from a lack of co-activation of the T-cells,
but this problem has now been remedied through the inclusion of co-stimulation domains on the
engineered CAR receptor (such as CD28 or CD3-zeta).
6) Altered Tumor Growth Pathways: In some cases, a tumor became resistant to therapy when the
tumor mutated to switch growth pathways. Thus, the original vaccine treatment attempting to block the
pathway failed. In these cases, perhaps the tumor resistance could be overcome by switching drugs to
block the new growth signaling pathway the tumor now depends on. This is especially a problem when
using antibody vaccines to block specific receptors. If the tumor is no longer dependent on that particular
signaling pathway, blocking the pathway’s receptor will not prevent tumor growth.
Cancer Vaccine Side-Effects
With respect to the topic of side-effects, our research shows that all types of cancer vaccines
cause adverse side-effects. The side-effects varied considerably, depending on the type of treatment and
the type of cancer, ranging from very mild and transient, to patient death in a few cases.
1) Patient Deaths: In clinical trial, three patients died from E. coli or Candida sepsis caused by treatment
with a CD19 x CD3 bispecific antibody that eliminated B-cells from the leukemia patients, hindering their
ability to make antibodies against the endogenous pathogens. And seven patients died in one year (2016)
in CAR clinical trials when the CAR cells caused fatal brain swelling. So, patient deaths indeed
occasionally occur with cancer vaccines, and these deaths are not unexpected for patients with relapsed
cancers. However, the patient deaths are rare from the vaccines, and most of our interviewees argued are
worth the cost of trying to save lives from certainly fatal relapsing cancers.
2) Cytokine-Release Syndrome: The second most serious side-effect seen with cancer vaccines is
cytokine release syndrome (CRS). CRS is a hyper-elevation of cytokine hormones that typically cause
fevers, hypotension, and hypoxia, but can be deadly when it causes organ failure. Although the cytokine
elevation is actually a desired outcome of cancer vaccines as an outcome of immune system activation,
the activation can become too prolonged and harm the patient. CRS was sometimes seen in the antibody
therapy trials, and in the adoptive T-cell therapies. In a large trial of patients with aggressive non-
Hodgkin’s lymphoma, about 18% of the patients developed CRS. But in most cases, the CRS was
treatable with corticosteroids (to lower inflammation) and with cytokine blocking antibodies (such as
anti-IL6-receptor antibody), so it was not usually life threatening.
3) Autoimmune Disorders: In the case of checkpoint vaccines, which are designed to ramp up the
patient’s immune system, one of the more serious side-effects observed was autoimmune disease (where
the patient’s immune system attacks the body). This is especially a problem with autoimmune
myocarditis, an immune attack on the heart, which can be fatal. While we identified a few papers that
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warned of such events, our interviews with physicians performing these therapies indicated they saw
these disorders only rarely in their patients.
Scientists are still trying to determine what causes the side-effects, but they appear to be caused
by a variety of mechanisms. In some cases, they appear to be caused by expression of the target antigen
in normal cells, thus those cells are destroyed by the therapy. Our interviews with scientists who designed
vaccines showed that designing a cancer vaccine that can only target a tumor cell expressing high antigen
levels while ignoring normal cells with medium expression levels of the antigen is not currently possible.
So, we recommend continuing the search for new target antigens that are only found in tumor cells and
not in normal cells.
In other cases, the killing of normal cells in the body appears to have resulted from a “bystander
effect”. In this case, the normal cells are killed due to their location near a targeted cell. This is
especially the case for antibody-drug conjugate vaccines (ADCs) where the highly cytotoxic drug can be
released nearby normal cells. While this killing could be beneficial if the bystander cell is a tumor cell no
longer expressing target antigen, in most cases the bystander effect is against normal tissue.
Overall, the side-effects in the vast majority of cases were relatively mild grade-1 and -2 events,
transient (lasting only a few days), and treatable. The side-effects were especially treatable if they were
detected early, so these events should be constantly monitored throughout the entire treatment. With
respect to whether the chance of side-effects should deter physicians from using these treatments, the
individuals interviewed for our project were strongly in favor of continuing the treatments, arguing that
the prognosis from the side-effects was far better than very poor prognosis they patients face from the
relapsing cancer. The side-effects they observed were relatively minor or rare, and are less important than
attempting to save the patient’s life from their relapsing cancer. As stated previously, most of the patients
participating in these cancer vaccine trials have run out of other treatment options.
Future Trends
We have observed several trends in the cancer vaccine field that hopefully will help solve some
of the problems mentioned above.
1) Combination Therapies. The simultaneous or consecutive use of two types of therapies has increased
drastically in the past few years. In some cases, the physicians are attempting to treat patients that have
down-regulated one target antigen by using an agent that targets a different antigen. In other cases, the
combination approach is designed to kill the tumor by two different mechanisms which hopefully will
synergize. A good example of this is the combined use of a checkpoint vaccine (to remove the immuno-
suppression caused by the tumor) with a second vaccine to target the tumor (such as a DC, TIL, or CAR).
2) Altered Method of Cell Killing: In some cases, tumor remission was achieved by switching from
recruiting T-cells to the tumor, to recruiting natural killer (NK) cells to do the killing. This has especially
been effective with bispecific antibodies, where one domain is against CD16A on NKs (to recruit them)
while the other domain is against CD30 (targeting the NKs to the lymphoma cells). The approach was
successful and is now being tried in other tumors.
3) Careful Patient Selection: Due to some of the mechanisms discussed above for tumors blocking the
immune system, a recent strategy is to closely monitor the patient’s tumor for potential upregulation of
inhibitors such as TGFβ, PD-1, PD-L1, or CTLA-4. When any of these are found to be elevated in the
tumor microenvironment, the appropriate modifier should be delivered, such as delivering antibodies
against TGFβ signaling if TGFβ is found to be elevated.
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4) Personalized Medicine: Neo-antigens are newly expressed proteins (or carbohydrates) on the surface
of tumor cells that form following DNA mutations. Because neo-antigens are not expressed during
human development, they are viewed as foreign in the body once they are expressed, so they make good
target antigens. The use of new rapid DNA sequencing methods allows a patient’s tumor cells to be
sequenced to analyze for neo-antigen formation, and if found, these could be used to prime DC or TIL
vaccines. But the process needs to be fast, as some patients have a very poor prognosis, and can die
within weeks.
5) CRISPR/Cas9 Editing of CAR T-Cells: One of the most promising and recent innovative uses of
CAR cells combines CAR receptor engineering with the use of CRISPR/cas9 gene editing technology to
eliminate a host gene. For example, the CRISPR system has been used to eliminate the gene TRAC
which is associated with allo-recognition in the body. Thus, its elimination could result in “universal”
CAR cells that could be used in any patient without rejection, eliminating the need to isolate the T-cells
from each patient.
6) Gut Microbiome: An interesting recent finding in the checkpoint inhibitor field is the discovery that
the gut microbiome, the type and quantity of bacteria present in the gut, strongly affects the response to
immune checkpoint therapy. The microbiota from mice non-responsive to checkpoint therapy when
transplanted into naïve mice induced them to become non-responders, and microbiota from responder
mice when transplanted into naïve mice made them become responders. One research team found that
mice with a gut microbiome enriched for Ruminococcaceae type bacteria respond better to checkpoint
therapy. Our interviews with the lead scientist of this study indicated he plans on moving into clinical
trials, either by supplementing the patient’s diet with this type of bacterium, or by using fecal microbiota
transplants (FMTs) enriched for this bacterium.
7) TIL Numbers and Composition: Several studies have shown that the presence of a high number of
tumor-infiltrating lymphocytes (TILs) in a patient’s tumor correlates with a better patient prognosis. This
finding has now been extended to show that treating patients with a high number of TILs is more effective
than using low numbers. In addition, we learned from our interviews that it is important to determine the
composition of the patient’s TILs, because a high number of infiltrating CD8+ (cytotoxic T-lymphocytes)
correlates with a good prognosis, while a high number of infiltrating neutrophils correlates with a poor
prognosis. It was recently shown that infiltrating neutrophils are of an N2 phenotype which is pro-
tumorigenic (promoting tumor angiogenesis, invasion, metastasis, and immunosuppression). So, it will be
important in future studies to assay for exactly which types of cells have migrated to the tumor site.
8) Tumor Location: Diffuse tumors such as lymphomas and leukemia have been treated by the
intravenous perfusion of cancer vaccines for several years now. But solid tumors are difficult to treat due
to challenges inherent to an organized tumor mass, such as abnormal vasculature, migration through a
dense stroma, and an elevated tumor interstitial pressure (IFP). It was recently shown that some of these
problems can be overcome by using a localized delivery of the vaccine directly into (or nearby) the solid
tumor. Our interviews indicated this localized delivery approach might also lower the incidence of side-
effects, as fewer tissues in the body would encounter the vaccine.
Overall, we conclude that cancer vaccines represent a fascinating method for fighting cancer, and
in some cases these approaches have provided complete remissions for relapsing cancers that are
impossible to treat using any other approach. The cancer vaccine field is complex (with treatments
ranging from simple antibody treatments, to genetically modifying T-cells), but the field provides a
variety of approaches for potentially treating a patient’s tumor. While each type of therapy can induce
side-effects in a portion of the patients, we agree with our interviewees that the side-effects are usually
minor, transient, and treatable, and are far less important than attempting to save the patient’s life from
their relapsing certainly fatal cancer.
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APPENDIX
SAMPLE QUESTIONS 1. Cancer Vaccine Side-Effects:
A. Do you agree that most cancer vaccines cause side-effects?
B. In your clinical trials have you observed any serious (grade-3 and grade-4) side-effects?
C. If the side-effects were serious, were they at least treatable (manageable)?
D. If the side-effects were manageable, does the potential for a cure for a patient with a fatal
disease outweigh the risk associated with a potentially fatal side-effect?
E. In your opinion, how can cancer vaccines be improved to cause fewer side-effects? Do we
need more research to identify target antigens on different types of cancers that are not
present in normal cells? Would a personalized medicine approach to identify patient-
specific neo-antigens on a patient’s tumor help decrease off target side-effects?
2. Lack of Vaccine Efficacy:
A. In some cases, a cancer vaccine appears to not work in a particular patient. In your opinion,
what kinds of events can cause this: loss of expression of the target antigen? Inactivation
of the perfused T-cells by the patient’s tumor cells? Lack of vaccine accessibility to a
solid tumor site?
B. For patients who do NOT respond to a cancer vaccine treatment, do you think it would be
beneficial to test a combination treatment with two or more vaccines that work by
different mechanisms?
3. Best Correlates of Protection:
A. It is not clear to us what factors best correlate with a vaccine’s success. For TIL and CAR T-
cell vaccines, some studies indicate success correlates best with a high load of TIL or
CAR cells. This suggests that developing methods for amplifying the number of T-cells
perfused into the patient should be a high priority. Other studies show the worst side-
effects occur at the highest T-cell doses. What is your opinion?
B. TIL vaccines isolated from a patient sometimes contain a mix of T-cells targeting a variety of
surface antigens, while engineered CAR vaccines typically target one key antigen. What
is your opinion about which strategy is best? Would the best approach vary from patient
to patient?
C. Some studies with TIL vaccines suggest that enriching and amplifying the T-cells from the
patient that are directed against a specific target antigen provide the best prognosis, while
other students suggest that using a mixture of TILs against a variety of antigens is most
successful. What is your opinion? How would we know which procedure to use in
advance?
4. Clinical Trial Patients:
A. Early cancer vaccine clinical trials have been criticized as having a relatively low number of
patients. Lately, the number of patients in cancer vaccine clinical trials has grown
exponentially to the point that some people worry there might not be a sufficient number
of refractory cancer patients to enroll in the trials. Do you think this is a problem?
5. Patient Chemoablation Treatments:
A. For TIL and CAR T-cell vaccines, some studies indicate that pre-treating the patient with
chemotherapy to obliterate (chemoablate) the patient’s own immune system prior to
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infusing the T-cell vaccine is critical for eliminating cells that can inhibit the vaccine.
Other studies indicate this pre-treatment is not needed. In your opinion, what dictates
when chemoablation should be used?
6. Immune Checkpoint Vaccines:
A. It appears that a recent trend in the cancer vaccine field has been to use combination vaccines
of 1) a checkpoint inhibitor plus 2) a vaccine against a specific target antigen. Do you
think this combination approach has been mostly successful?
B. What do you think of the recent failed Incyte Phase-III clinical trial using a PD-1 inhibitor
(Opdivo) plus an inhibitor of the enzyme IDO? Their phase-I and II data looked very
promising, but the phase-III data with the combination was no better than Opdivo alone.
What is your opinion?
C. Immune checkpoint vaccines have been shown in some cases to cause an over-activation of the
immune system (such as inflammation). Do you now routinely monitor for these effects?
7. Personalized Medicine:
A. Some scientists argue that cancer surface antigens vary from patient to patient, thus using a
personalized medicine approach to identify a patient’s own surface antigens is better than
using a vaccine that targets a generic surface antigen. But how expensive is this
personalized approach? It must be expensive to sequence the DNA from a patient’s
tumor to identify “neo-antigens” present on that particular tumor.
B. How long does a typical DNA genome (exome) sequencing project take? Our readings
indicate it can take weeks to sequence the DNA, analyze it for neo-antigen formation, and
synthesize the neo-antigens chemically. Some patients don’t have weeks to live, so
should the speed of this approach be accelerated?
INTERVIEW PREAMBLE
We are a group of students from the Worcester Polytechnic Institute in Massachusetts, and for our
research project we are conducting a series of interviews to investigate problems associated with the field
of cancer vaccines which have recently shown both strong successes and failures.
Your participation in this interview is completely voluntary, and you may withdraw at any time.
During this interview, we would like to record our conversation for later analysis. We will also be taking
notes during the interview on key points. Is this okay with you?
Can we also have your permission to quote any comments or perspectives expressed during the
interview? This information will be used for research purposes only, and we will give you an opportunity
to review any materials we use prior to the completion of our final report, which will be published on-line
in WPI’s archive of projects.
If the subject does not agree to be quoted, we will respond as follows: “Since you would not like
to be quoted during this interview, we will make sure your responses are anonymous. No names or
identifying information will appear in any of the project reports or publications.”
Your participation and assistance is greatly appreciated, and we thank you for taking the time to
meet with us. If you are interested, we would be happy to provide you with a copy of our results at the
conclusion of our study.